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1. Automatingand optimizing pile group design using a Genetic Algorithm Abedin, Arian PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_0_j_idt591",{id:"formSmash:items:resultList:0:j_idt591",widgetVar:"widget_formSmash_items_resultList_0_j_idt591",onLabel:"Abedin, Arian ",offLabel:"Abedin, Arian ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_0_j_idt594",{id:"formSmash:items:resultList:0:j_idt594",widgetVar:"widget_formSmash_items_resultList_0_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:0:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Ligai, WolmirKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:0:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Automatingand optimizing pile group design using a Genetic Algorithm2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_0_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:0:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_0_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); In bridge design, a set of piles is referred to as a pile group. The design process of pile groups employed by many firms is currently manual, time consuming, and produces pile groups that are not robust against placement errors.

This thesis applies the metaheuristic method Genetic Algorithm to automate and improve the design of pile groups for bridge column foundations. A software is developed and improved by implementing modifications to the Genetic Algorithm. The algorithm is evaluated by the pile groups it produces, using the Monte Carlo method to simulate errors for the purpose of testing the robustness. The results are compared with designs provided by the consulting firm Tyrens AB.

The software is terminated manually, and generally takes less than half an hour to produce acceptable pile groups. The developed Genetic Algorithm Software produces pile groups that are more robust than the manually designed pile groups to which they are compared, using the Monte Carlo method. However, due to the visually disorganized designs, the pile groups produced by the algorithm may be di cult to get approved by Trafikverket. The software might require further modifications addressing this problem before it can be of practical use.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:0:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_0_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:0:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_0_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:0:j_idt854:0:fullText"});}); 2. Learning to solve inverse problems using Wasserstein loss Adler, Jonas PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_1_j_idt591",{id:"formSmash:items:resultList:1:j_idt591",widgetVar:"widget_formSmash_items_resultList_1_j_idt591",onLabel:"Adler, Jonas ",offLabel:"Adler, Jonas ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_1_j_idt594",{id:"formSmash:items:resultList:1:j_idt594",widgetVar:"widget_formSmash_items_resultList_1_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics (Div.). Elekta, Box 7593, 103 93 Stockholm, Sweden.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:1:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Ringh, AxelKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.Öktem, OzanKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics (Div.).Karlsson, JohanKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:1:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Learning to solve inverse problems using Wasserstein lossManuscript (preprint) (Other academic)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_1_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:1:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_1_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); We propose using the Wasserstein loss for training in inverse problems. In particular, we consider a learned primal-dual reconstruction scheme for ill-posed inverse problems using the Wasserstein distance as loss function in the learning. This is motivated by miss-alignments in training data, which when using standard mean squared error loss could severely degrade reconstruction quality. We prove that training with the Wasserstein loss gives a reconstruction operator that correctly compensates for miss-alignments in certain cases, whereas training with the mean squared error gives a smeared reconstruction. Moreover, we demonstrate these effects by training a reconstruction algorithm using both mean squared error and optimal transport loss for a problem in computerized tomography.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:1:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 3. Test Case Prioritization as a Mathematical Scheduling Problem Ahlberg, Marcus PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_2_j_idt591",{id:"formSmash:items:resultList:2:j_idt591",widgetVar:"widget_formSmash_items_resultList_2_j_idt591",onLabel:"Ahlberg, Marcus ",offLabel:"Ahlberg, Marcus ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_2_j_idt594",{id:"formSmash:items:resultList:2:j_idt594",widgetVar:"widget_formSmash_items_resultList_2_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:2:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Fornander, EricKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:2:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Test Case Prioritization as a Mathematical Scheduling Problem2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_2_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:2:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_2_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Software testing is an extremely important phase of product development where the objective is to detect hidden bugs. The usually high complexity of today’s products makes the testing very resource intensive since numerous test cases have to be generated in order to detect all potential faults. Therefore, improved strategies of the testing process is of high interest for many companies. One area where there exists potential for improvement is the order by which test cases are executed to detect faults as quickly as possible, which in research is known as the test case prioritization problem. In this thesis, an extension to this problem is studied where dependencies between test cases are present and the processing times of the test cases are known. As a first result of the thesis, a mathematical model of the test case prioritization problem with dependencies and known processing times as a mathematical scheduling problem is presented. Three different solution algorithms to this problem are subsequently evaluated: A Sidney decomposition algorithm, an own-designed heuristic algorithm and an algorithm based on Smith’s rule. The Sidney decomposition algorithm outper-formed the others in terms of execution time of the algorithm and objective value of the generated schedule. The evaluation was conducted by simulation with artificial test suites and via a case study in industry through a company in the railway domain.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:2:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_2_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:2:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_2_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:2:j_idt854:0:fullText"});}); 4. Lageroptimering Ahlberg, Marcus PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_3_j_idt591",{id:"formSmash:items:resultList:3:j_idt591",widgetVar:"widget_formSmash_items_resultList_3_j_idt591",onLabel:"Ahlberg, Marcus ",offLabel:"Ahlberg, Marcus ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_3_j_idt594",{id:"formSmash:items:resultList:3:j_idt594",widgetVar:"widget_formSmash_items_resultList_3_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:3:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Lilja, JimmyKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:3:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Lageroptimering: Minimera tiden till leverans med begränsat lagerutrymme2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_3_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:3:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_3_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This thesis presents a study in mathematical optimization of the inventory routine at the company Aktiebolaget Kronborsten. The thesis establishes a general optimization problem identified at Kronborstens inventory routine. The identified problem is to find the optimal mix between products in the finished goods inventory, which minimizes the expected time until delivery.

The proposed model assumes that orders and manufacturing follow a stochastic process. With these assumptions the inventory and manufacturing are represented as several independent Markov processes. From the stationary distribution of these processes a function was identified for the expected time until delivery for a given solution. The identified function had convex properties which made it possible to solve the optimization problem using the marginal allocation algorithm.

The mathematical problem is followed by a chapter about the costs related to storage. The purpose of this chapter is to help Kronborsten to valuate their options and consequences of strategical decisions about the inventory levels.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:3:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_3_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:3:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_3_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:3:j_idt854:0:fullText"});}); 5. ESG-investerande och portföljresultat Ahlin, Filip PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_4_j_idt591",{id:"formSmash:items:resultList:4:j_idt591",widgetVar:"widget_formSmash_items_resultList_4_j_idt591",onLabel:"Ahlin, Filip ",offLabel:"Ahlin, Filip ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_4_j_idt594",{id:"formSmash:items:resultList:4:j_idt594",widgetVar:"widget_formSmash_items_resultList_4_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:4:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Wahlstedt, AntonKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:4:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); ESG-investerande och portföljresultat: En studie av ESG-investerande utifrån metoden bäst-i-klassen2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_4_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:4:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_4_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); As a result of a more globalized and industrial world, sustainability issues in terms of the environment and society has become an everyday heading in the financial world. The fact that companies should work actively towards sustainability and accountability is today a necessity rather than a choice. The purpose of this study is to research responsible investment (RI) and portfolio performance. To examine this relationship the study focuses on ESG where its dimensions will be included jointly through optimization, discussion and conclusion. The report outlines how ESG can be integrated into the investment process, but the weight of the study addresses the discussion of a portfolio's performance at the inclusion of ESG. Methods used are Modern Portfolio Theory (MPT) combined with the implementation of ESG according to "best-in-class". The results of the study lead towards the conclusion that ESG in addition to its positive effects, provided an accurate assessment, on sustainability also is financially arguable for investors.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:4:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_4_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:4:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_4_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:4:j_idt854:0:fullText"});}); 6. Modellering och kundprocessanalys av kösystem på Vapiano Sturegatan Ahlklo, Yrr PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_5_j_idt591",{id:"formSmash:items:resultList:5:j_idt591",widgetVar:"widget_formSmash_items_resultList_5_j_idt591",onLabel:"Ahlklo, Yrr ",offLabel:"Ahlklo, Yrr ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_5_j_idt594",{id:"formSmash:items:resultList:5:j_idt594",widgetVar:"widget_formSmash_items_resultList_5_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:5:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Lind, CarinKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:5:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Modellering och kundprocessanalys av kösystem på Vapiano Sturegatan2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_5_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:5:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_5_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); In this Bachelorthesis, the queuing system of Vapiano Sturegatan has been analysed. The customers of the restaurant experience long waiting times during lunchtime, which is a problem Vapiano Sturegatan recognises. The purpose of this report is to suggest and analyse possible improvements of the queueing system in order to reduce this problem.

The current queuing system was approximated with markovian queuing models. Both an M/M/2-and an M/M/8-approach were considered, which of the M/M/2-model was deemed most reliable. The expected time in the system was calculated for different modications of Vapiano Sturegatan's current queuing system setup. They led to the conclusion that adding capacity to every serving station would be the best improvement to their current system, instead of adding an extra station. Furthermore, other queuing systems are considered and analysed from a customer process perspective. To improve the flow of customers in the restaurant, this report suggests an electronic queuing system. As long as the suggested system is implemented with careful planning and evaluation, the advantages of the electronic system exceed the benefit of simplicity of the current queuing system.

This thesis will be delivered to Vapiano Sturegatan. The authors hope that the results can beneficial in the planning of future restaurants and changes of the queuing system.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:5:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_5_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:5:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_5_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:5:j_idt854:0:fullText"});}); 7. Topology optimization of load-carryingstructures using three different typesof finite elements Ahmed, Shoaib PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_6_j_idt591",{id:"formSmash:items:resultList:6:j_idt591",widgetVar:"widget_formSmash_items_resultList_6_j_idt591",onLabel:"Ahmed, Shoaib ",offLabel:"Ahmed, Shoaib ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:6:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:6:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Topology optimization of load-carryingstructures using three different typesof finite elements2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_6_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:6:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_6_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This thesis deals with topology optimization of load-carrying structures, in particular compliance minimization subject to a constraint on the total amount of material to be used. The main purpose of the work was to compare the following three types of finite elements for the above topology optimization problems: Four node square elements with bilinear shape functions, nine node square elements with quadratic shape functions, and six node hexagonal elements with Wachspress shape functions. The SIMP approach (Solid Isotropic Material with Penalization) was used to model the topology optimization problem for different load and support conditions, and the method of moving asymptotes (MMA) was used to solve the formulated optimization problems. On the considered test problems, it turned out that the results obtained by using six node hexagonal elements were in general better than the corresponding results using nine node square elements which in turn were better than the results using four node square elements. The price paid for the improvements were increased computation times.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:6:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_6_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:6:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_6_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:6:j_idt854:0:fullText"});}); 8. Integration of Production Scheduling and Energy Management Ait-Ali, Abderrahman PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_7_j_idt591",{id:"formSmash:items:resultList:7:j_idt591",widgetVar:"widget_formSmash_items_resultList_7_j_idt591",onLabel:"Ait-Ali, Abderrahman ",offLabel:"Ait-Ali, Abderrahman ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:7:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:7:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Integration of Production Scheduling and Energy Management: Software Development2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_7_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:7:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_7_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Demand-Side Management concepts have the potential to positively impact the financial as well as the environmental aspects of energy-intensive industries. More specifically, they allow reducing the energy cost for the industrial plants by dealing with energy-availability fluctuations.

In this context, efficient frameworks for scheduling with energy awareness have been studied and showed potential to reduce the overall energy bill for energy-intensive industries, for instance stainless steel and paper plants. Those frameworks usually combine scheduling and energy optimization into one monolithic system. This work investigates the possibility of integrating the two systems by specific exchange of signals, while keeping the scheduling model separated from the energy-cost optimization model. Such integration means that the pre-existent schedulers and energy optimizers could be easily modified and reused without re-implementing the whole new system.

Two industrial problems with different scheduling approaches are studied. The first problem is about pulp and paper production which uses the Resource Task Network (RTN) scheduling approach. The second one is about stainless steel production which is based on a bi-level heuristic implementation of an improved energy-aware scheduler. This work presents the decomposition methods that are available in literature and their application to the two industrial problems. Besides an improvement in the RTN approach for handling storages, this thesis describes a prototype implementation of the energy-aware RTN scheduler for paper and pulp production. Furthermore, this work investigates the performance of the application of different decomposition methods on different problem instances.

The numerical case studies show that even though the decomposition decreases the solution quality compared to the monolithic system, it still gives good solutions within an acceptable duration with the advantage of having two separate pre-existent systems which are simply exchanging signals.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:7:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_7_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:7:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_7_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:7:j_idt854:0:fullText"});}); 9. Study and Industrialization of Computational Methods for Orbital Maneuvers Ait-Lakbir, Hanane PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_8_j_idt591",{id:"formSmash:items:resultList:8:j_idt591",widgetVar:"widget_formSmash_items_resultList_8_j_idt591",onLabel:"Ait-Lakbir, Hanane ",offLabel:"Ait-Lakbir, Hanane ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:8:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:8:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Study and Industrialization of Computational Methods for Orbital Maneuvers2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_8_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:8:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_8_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The use of electric propulsion is a watershed in the space field. Indeed, due to its eÿciency in term of mass consumption, the actors of the space industries see in this piece of technology a means to manufacture lighter satellites and to launch them at lower cost. To face with this new market, industries need to develop new tools to handle these satellites and their missions. This report will elaborate on the methods used to compute maneuvers for all-electric spacecraft.

One of the main phases during satellite operations is maneuvering to ensure on the one hand a correct configuration to achieve the mission and on the other hand the integrity of the satellite. The present work is focused on the computation of the orbital maneuvers during the early phase of the mission: orbit raising. Due to the characteristics of electric propulsion, an overall approach provided by the application of the optimal control theory is required to compute these maneuvers performed by low-thrust engines. This report will develop the use of an indirect method based on the Pontryagin minimum principle. Two types of problems related to the constraints during the space missions are presented. Because electric maneuvers are longer than chemical maneuvers, it is usually necessary to seek to minimize the duration of a maneuver. The second interesting performance is the remaining propellant mass to achieve the mission: therefore, the minimization of the mass consumption during the maneuver is the second performance considered in the report.

During the internship, a JAVA implementation of the resolution of these two problems has been done. The report will present the preliminary results as well as the encountered difficulties and some possible solutions.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:8:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_8_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:8:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_8_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:8:j_idt854:0:fullText"});}); 10. Cost Effective Simulation-Based Multiobjective Optimization in Performance of Internal Combustion Engine Aittokoski, Timo PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_9_j_idt591",{id:"formSmash:items:resultList:9:j_idt591",widgetVar:"widget_formSmash_items_resultList_9_j_idt591",onLabel:"Aittokoski, Timo ",offLabel:"Aittokoski, Timo ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_9_j_idt594",{id:"formSmash:items:resultList:9:j_idt594",widgetVar:"widget_formSmash_items_resultList_9_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Department of Mathematical Information Technology, University of Jyväskylä, Finland.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:9:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Miettinen, KaisaKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:9:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Cost Effective Simulation-Based Multiobjective Optimization in Performance of Internal Combustion Engine2008In: Engineering optimization (Print), ISSN 0305-215X, E-ISSN 1029-0273, Vol. 40, no 7, p. 593-612Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_9_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:9:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_9_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Solving real-life engineering problems requires often multiobjective, global, and efficient (in terms of objective function evaluations) treatment. In this study, we consider problems of this type by discussing some drawbacks of the current methods and then introduce a new population-based multiobjective optimization algorithm UPS-EMOA which produces a dense (not limited to the population size) approximation of the Pareto-optimal set in a computationally effective manner.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:9:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 11. Clustering aided approach for decision making in computationally expensive multiobjective optimization Aittokoski, Timo PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_10_j_idt591",{id:"formSmash:items:resultList:10:j_idt591",widgetVar:"widget_formSmash_items_resultList_10_j_idt591",onLabel:"Aittokoski, Timo ",offLabel:"Aittokoski, Timo ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_10_j_idt594",{id:"formSmash:items:resultList:10:j_idt594",widgetVar:"widget_formSmash_items_resultList_10_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Department of Mathematical Information Technology, University of Jyväskylä, Finland.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:10:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Äyrämö, SamiDepartment of Mathematical Information Technology, University of Jyväskylä, Finland.Miettinen, KaisaKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:10:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Clustering aided approach for decision making in computationally expensive multiobjective optimization2009In: Optimization Methods and Software, ISSN 1055-6788, E-ISSN 1029-4937, Vol. 24, no 2, p. 157-174Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_10_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:10:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_10_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Typically, industrial optimization problems need to be solved in an efficient, multiobjective and global manner, because they are often computationally expensive (as function values are typically based on simulations), they may contain multiple conflicting objectives, and they may have several local optima. Solving such problems may be challenging and time consuming when the aim is to find the most preferred Pareto optimal solution.

In this study, we propose a method where we use an advanced clustering technique to reveal essential characteristics of the approximation of the Pareto optimal set, which has been generated beforehand. Thus, the decision maker (DM) is involved only after the most time consuming computation is finished. After the initiation phase, a moderate number of cluster prototypes projected to the Pareto optimal set is presented to the DM to be studied. This allows him/her to rapidly gain an overall understanding of the main characteristics of the problem without placing too much cognitive load on the DM. Furthermore, we also suggest some ways of applying our approach to different types of problems and demonstrate it with an example related to internal combustion engine design.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:10:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 12. A branch-and-cut method for the Vehicle Relocation Problem in the One-Way Car-Sharing Albinski, Szymon Janusz PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_11_j_idt591",{id:"formSmash:items:resultList:11:j_idt591",widgetVar:"widget_formSmash_items_resultList_11_j_idt591",onLabel:"Albinski, Szymon Janusz ",offLabel:"Albinski, Szymon Janusz ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:11:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:11:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); A branch-and-cut method for the Vehicle Relocation Problem in the One-Way Car-Sharing2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_11_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:11:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_11_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The purpose of this thesis is to develop an algorithm which solves the Vehicle Relocation Problem in the One-Way Car-Sharing (VRLPOWCS) as fast as possible. The problem describes the task of relocating the cars to areas with the largest demand. The chauffeurs who relocate the cars are transported by shuttle buses. Each car is assigned an individual relocation utility. The objective is to find shuttle tours that maximise in a given time the relocation utility while balancing the distribution of the cars. The VRLPOWCS is formulated as a mixed integer linear program. Since this problem is NP

*-complete*we choose the branch-and-cut method to solve it. Using additional cutting planes – which exploit the structure of the VRLPOWCS – we enhance this method. Tests on real data show that this extended algorithm can solve the VRLPOWCS faster.PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:11:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_11_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:11:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_11_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:11:j_idt854:0:fullText"});}); 13. Interior point algorithms Aleman, Dionne M.et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_12_j_idt594",{id:"formSmash:items:resultList:12:j_idt594",widgetVar:"widget_formSmash_items_resultList_12_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:12:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Glaser, DanielKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.Romeijn, H. EdwinDempsey, James F.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:12:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Interior point algorithms: guaranteed optimality for fluence map optimization in IMRT2010In: Physics in Medicine and Biology, ISSN 0031-9155, E-ISSN 1361-6560, Vol. 55, no 18, p. 5467-5482Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_12_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:12:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_12_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); One of the most widely studied problems of the intensity-modulated radiation therapy (IMRT) treatment planning problem is the fluence map optimization (FMO) problem, the problem of determining the amount of radiation intensity, or fluence, of each beamlet in each beam. For a given set of beams, the fluences of the beamlets can drastically affect the quality of the treatment plan, and thus it is critical to obtain good fluence maps for radiation delivery. Although several approaches have been shown to yield good solutions to the FMO problem, these solutions are not guaranteed to be optimal. This shortcoming can be attributed to either optimization model complexity or properties of the algorithms used to solve the optimization model. We present a convex FMO formulation and an interior point algorithm that yields an optimal treatment plan in seconds, making it a viable option for clinical applications.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:12:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 14. A fluence map optimization model for restoring traditional fractionation in IMRT treatment planning Aleman, Dionne M.et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_13_j_idt594",{id:"formSmash:items:resultList:13:j_idt594",widgetVar:"widget_formSmash_items_resultList_13_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:13:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Wallgren, JohanKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.Romeijn, H. EdwinDempsey, James F.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:13:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); A fluence map optimization model for restoring traditional fractionation in IMRT treatment planning2014In: Optimization Letters, ISSN 1862-4472, E-ISSN 1862-4480, Vol. 8, no 4, p. 1453-1473Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_13_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:13:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_13_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); One of the core problems in intensity modulated radiation therapy (IMRT) treatment planning is the fluence map optimization (FMO) problem, which determines a fluence map (or profile) for each beam used in the delivery of treatment. Radiation therapy is administered in multiple so-called daily fractions to allow for healthy tissue to recover from damage caused by the treatment. Before the advent of IMRT, the treatment was designed to ensure a constant dose to cells in the target (the areas in the patient where cancerous cells are present or suspected). In the presence of multiple targets with different prescribed doses, this design meant that treatment had to be delivered in a sequence of unequal fractions, one per prescription dose level. For example, in case of two targets treatment would consist of an initial plan aimed at treating both targets to a lower total dose, followed by a so-called boost plan aimed at delivering the additional dose at the target with higher prescribed dose. In contrast, IMRT treatment plans are often delivered with equal treatment plan for each fraction, which means that the dose per fraction cannot be the same for all targets. The important problem of restoring traditional fractionation to IMRT treatments has not yet received much attention in the literature. In this paper we propose a new optimization model that explicitly restores fractionation into the FMO problem, yielding an optimal set of fluence maps for each fraction. We illustrate the capabilities of our approach on clinical head-and-neck cancer cases.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:13:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 15. Combinatorial and price efficient optimization of the underlying assets in basket options Alexis, Sara PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_14_j_idt591",{id:"formSmash:items:resultList:14:j_idt591",widgetVar:"widget_formSmash_items_resultList_14_j_idt591",onLabel:"Alexis, Sara ",offLabel:"Alexis, Sara ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:14:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:14:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Combinatorial and price efficient optimization of the underlying assets in basket options2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_14_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:14:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_14_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The purpose of this thesis is to develop an optimization model that chooses the optimal and price efficient combination of underlying assets for a equally weighted basket option.

To obtain a price efficient combination of underlying assets a function that calculates the basket option price is needed, for further use in an optimization model. The closed-form basket option pricing is a great challenge, due to the lack of a distribution describing the augmented stochastic price process. Many types of approaches to price an basket option has been made. In this thesis, an analytical approximation of the basket option price has been used, where the analytical approximation aims to develop a method to describe the augmented price process. The approximation is done by moment matching, i.e. matching the first two moments of the real distribution of the basket option with an lognormal distribution. The obtained price function is adjusted and used as the objective function in the optimization model.

Furthermore, since the goal is to obtain en equally weighted basket option, the appropriate class of optimization models to use are binary optimization problems. This kind of optimization model is in general hard to solve - especially for increasing dimensions. Three different continuous relaxations of the binary problem has been applied in order to obtain continuous problems, that are easier to solve.

The results shows that the purpose of this thesis is fulfilled when formulating and solving the optimization problem - both as an binary and continuous nonlinear optimization model. Moreover, the results from a Monte Carlo simulation for correlated stochastic processes shows that the moment matching technique with a lognormal distribution is a good approximation for pricing a basket option.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:14:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_14_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:14:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_14_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:14:j_idt854:0:fullText"});}); 16. Optimering av antal flygplanssäten Alexis, Sara PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_15_j_idt591",{id:"formSmash:items:resultList:15:j_idt591",widgetVar:"widget_formSmash_items_resultList_15_j_idt591",onLabel:"Alexis, Sara ",offLabel:"Alexis, Sara ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_15_j_idt594",{id:"formSmash:items:resultList:15:j_idt594",widgetVar:"widget_formSmash_items_resultList_15_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:15:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Uludag, EbruKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:15:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Optimering av antal flygplanssäten:*Modellering med avseende på yta, intäkt och efterfrågan*2014Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_15_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:15:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_15_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); When managing the number of seats in a plane it is important to take into account the passenger intensity, i.e. how tightly the seats are located. The critical variable for these decisions is the distance between a point on one seat and the same point on the next seat. Critical variables that have small values , i.e. short distance, means more rows of seats and thus higher profits. Any unused space is an expensive waste due to the fact that the difference between profit and loss for a given flight can be as little as less than a cost of a seat.

The purpose of this thesis is to develop a mathematical model to find the optimal seat allocation between classes in an airplane. The modeling shall be performed so that the revenues for the airlines and usage of the surface of the cabin are maximized and yet meet demand. This thesis also aims to investigate which different market strategies of airlines there are and how these affect the seat allocation.

The report shows that the revenue and demand are not the only factors that affect the optimal number of seats for a class, but that there are also external factors that may play a role. The model's ranking in reality is difficult to assess because of the lack of realistic and reliable data that can be used for a basis for decisions

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:15:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_15_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:15:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_15_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:15:j_idt854:0:fullText"});}); 17. Team KTH’s Picking Solution for the Amazon Picking Challenge 2016 Almeida, Diogo PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_16_j_idt591",{id:"formSmash:items:resultList:16:j_idt591",widgetVar:"widget_formSmash_items_resultList_16_j_idt591",onLabel:"Almeida, Diogo ",offLabel:"Almeida, Diogo ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_16_j_idt594",{id:"formSmash:items:resultList:16:j_idt594",widgetVar:"widget_formSmash_items_resultList_16_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:16:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Ambrus, RaresKTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.Caccamo, SergioKTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.Chen, XiKTH.Cruciani, SilviaPinto Basto De Carvalho, Joao FKTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.Haustein, JoshuaKTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.Marzinotto, AlejandroKTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.Vina, FranciscoKTH.Karayiannidis, YannisKTH.Ögren, PetterKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.Jensfelt, PatricKTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.Kragic, DanicaKTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:16:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Team KTH’s Picking Solution for the Amazon Picking Challenge 20162017In: Warehouse Picking Automation Workshop 2017: Solutions, Experience, Learnings and Outlook of the Amazon Robotics Challenge, 2017Conference paper (Other (popular science, discussion, etc.))Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_16_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:16:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_16_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); In this work we summarize the solution developed by Team KTH for the Amazon Picking Challenge 2016 in Leipzig, Germany. The competition simulated a warehouse automation scenario and it was divided in two tasks: a picking task where a robot picks items from a shelf and places them in a tote and a stowing task which is the inverse task where the robot picks items from a tote and places them in a shelf. We describe our approach to the problem starting from a high level overview of our system and later delving into details of our perception pipeline and our strategy for manipulation and grasping. The solution was implemented using a Baxter robot equipped with additional sensors.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:16:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 18. Alternative Methods for Operational Optimization of Hydro Power Plants Almgrund, Jonas PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_17_j_idt591",{id:"formSmash:items:resultList:17:j_idt591",widgetVar:"widget_formSmash_items_resultList_17_j_idt591",onLabel:"Almgrund, Jonas ",offLabel:"Almgrund, Jonas ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:17:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:17:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Alternative Methods for Operational Optimization of Hydro Power Plants2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_17_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:17:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_17_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The aim of this thesis is to optimize hydro power plants with data generated from observations and field tests at the plants. The output is optimal production tables and curves in order to operate and plan hydro power plants in an optimized way concerning power output, efficiency and distribution of water. The thesis is performed in collaboration with Vattenfall AB, which currently use an internal optimization program called SEVAP. Two alternative methods have been selected, employed and compared with the current optimization program, these are Interior-Point Method and Sequential Quadratic Programming. Three start-point strategies are created to increase the probability of finding a global optima. A heuristic rule is used for selection of strategy in order to prevent rapid changes in load distribution for small variations in dispatched water. The optimization is performed at three plants in Sweden with different size and setup. The results of this evaluation showed marginally better results for the employed methods in comparison to the currently used optimization. Further, the developed program is more flexible and compatible to integrate with future digitalization projects.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:17:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_17_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:17:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_17_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:17:j_idt854:0:fullText"});}); 19. Optimal separation of points Al-Mosawi, Masar PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_18_j_idt591",{id:"formSmash:items:resultList:18:j_idt591",widgetVar:"widget_formSmash_items_resultList_18_j_idt591",onLabel:"Al-Mosawi, Masar ",offLabel:"Al-Mosawi, Masar ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:18:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:18:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Optimal separation of points2012Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_18_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:18:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_18_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); How should n points be distributed in a given region F in R^d such that they are separated as much as possible?

This general problem is studied in this paper, for some combinations of F, d, n, and the ways one can state the problem mathematically. Some numerical optimization methods are suggested and tested, both on the point separation problem and the closely related circle packing problem. The results are compared with some known analytical results. The main conclusion is that the suggested numerical methods are useful general tools to obtain optimal solutions to the considered problems.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:18:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_18_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:18:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_18_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:18:j_idt854:0:fullText"});}); 20. Application of model predictive control and analysis of switched systems to the direct voltage control of AC-DC converters Almér, S.et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_19_j_idt594",{id:"formSmash:items:resultList:19:j_idt594",widgetVar:"widget_formSmash_items_resultList_19_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:19:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Mariéthoz, S.Morari, M.Jönsson, UlfKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:19:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Application of model predictive control and analysis of switched systems to the direct voltage control of AC-DC converters2015In: 2009 European Control Conference, ECC 2009, 2015, p. 3593-3598Conference paper (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_19_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:19:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_19_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Recent tools for control and analysis of hybrid systems are applied to an AC-DC converter. The topology poses particularly challenging problems since it is unusually complex and the circuit parameters are such that the dynamic coupling between the AC and DC sides cannot be ignored. The paper proposes a model predictive control scheme for direct voltage control which circumvents the bandwidth limitations associated with classical cascade control. The stability and harmonic properties of the resulting closed loop system are investigated using new tools for the analysis of switched systems.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:19:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 21. Control and Analysis of Pulse-Modulated Systems Almér, Stefan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_20_j_idt591",{id:"formSmash:items:resultList:20:j_idt591",widgetVar:"widget_formSmash_items_resultList_20_j_idt591",onLabel:"Almér, Stefan ",offLabel:"Almér, Stefan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:20:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:20:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Control and Analysis of Pulse-Modulated Systems2008Doctoral thesis, comprehensive summary (Other scientific)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_20_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:20:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_20_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The thesis consists of an introduction and four appended papers. In the introduction we give an overview of pulse-modulated systems and provide a few examples of such systems. Furthermore, we introduce the so-called dynamic phasor model which is used as a basis for analysis in two of the appended papers. We also introduce the harmonic transfer function and finally we provide a summary of the appended papers.

The first paper considers stability analysis of a class of pulse-width modulated systems based on a discrete time model. The systems considered typically have periodic solutions. Stability of a periodic solution is equivalent to stability of a fixed point of a discrete time model of the system dynamics.

Conditions for global and local exponential stability of the discrete time model are derived using quadratic and piecewise quadratic Lyapunov functions. A griding procedure is used to develop a systematic method to search for the Lyapunov functions.

The second paper considers the dynamic phasor model as a tool for stability analysis of a general class of pulse-modulated systems. The analysis covers both linear time periodic systems and systems where the pulse modulation is controlled by feedback. The dynamic phasor model provides an $\textbf{L}_2$-equivalent description of the system dynamics in terms of an infinite dimensional dynamic system. The infinite dimensional phasor system is approximated via a skew truncation. The truncated system is used to derive a systematic method to compute time periodic quadratic Lyapunov functions.

The third paper considers the dynamic phasor model as a tool for harmonic analysis of a class of pulse-width modulated systems. The analysis covers both linear time periodic systems and non-periodic systems where the switching is controlled by feedback. As in the second paper of the thesis, we represent the switching system using the L_2-equivalent infinite dimensional system provided by the phasor model. It is shown that there is a connection between the dynamic phasor model and the harmonic transfer function of a linear time periodic system and this connection is used to extend the notion of harmonic transfer function to describe periodic solutions of non-periodic systems. The infinite dimensional phasor system is approximated via a square truncation. We assume that the response of the truncated system to a periodic disturbance is also periodic and we consider the corresponding harmonic balance equations. An approximate solution of these equations is stated in terms of a harmonic transfer function which is analogous to the harmonic transfer function of a linear time periodic system. The aforementioned assumption is proved to hold for small disturbances by proving the existence of a solution to a fixed point equation. The proof implies that for small disturbances, the approximation is good.

Finally, the fourth paper considers control synthesis for switched mode DC-DC converters. The synthesis is based on a sampled data model of the system dynamics. The sampled data model gives an exact description of the converter state at the switching instances, but also includes a lifted signal which represents the inter-sampling behavior. Within the sampled data framework we consider H-infinity control design to achieve robustness to disturbances and load variations. The suggested controller is applied to two benchmark examples; a step-down and a step-up converter. Performance is verified in both simulations and in experiments.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:20:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)FULLTEXT01$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_20_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:20:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_20_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:20:j_idt854:0:fullText"});}); 22. Sampled data control of DC-DC converters Almér, Stefan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_21_j_idt591",{id:"formSmash:items:resultList:21:j_idt591",widgetVar:"widget_formSmash_items_resultList_21_j_idt591",onLabel:"Almér, Stefan ",offLabel:"Almér, Stefan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:21:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:21:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Sampled data control of DC-DC convertersArticle in journal (Other academic)23. Hybrid control techniques for switched-mode DC-DC converters part I Almér, Stefan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_22_j_idt591",{id:"formSmash:items:resultList:22:j_idt591",widgetVar:"widget_formSmash_items_resultList_22_j_idt591",onLabel:"Almér, Stefan ",offLabel:"Almér, Stefan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_22_j_idt594",{id:"formSmash:items:resultList:22:j_idt594",widgetVar:"widget_formSmash_items_resultList_22_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:22:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Fujioka, HisayaKTH. Kyoto University, Japan.Jönsson, UlfKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.Kao, Chung YaoKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.Patino, D.Riedinger, P.Geyer, T.Beccuti, A.Papafotiou, G.Morari, M.Wernrud, A.Rantzer, A.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:22:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Hybrid control techniques for switched-mode DC-DC converters part I: The step-down topology2007In: 2007 American Control Conference, IEEE , 2007, p. 5450-5457Conference paper (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_22_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:22:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_22_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Several recent techniques from hybrid and optimal control are evaluated on a power electronics benchmark problem. The benchmark involves a number of practically interesting operating scenarios for a fixed-frequency synchronous step-down dc-dc converter. The specifications are defined such that good performance only can be obtained if the switched and nonlinear nature of the problem is respected during the design phase.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:22:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 24. Dynamic Phasor Analysis Of Pulse-Modulated Systems Almér, Stefanet al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_23_j_idt594",{id:"formSmash:items:resultList:23:j_idt594",widgetVar:"widget_formSmash_items_resultList_23_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:23:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Jönsson, UlfKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:23:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Dynamic Phasor Analysis Of Pulse-Modulated Systems2012In: SIAM Journal of Control and Optimization, ISSN 0363-0129, E-ISSN 1095-7138, Vol. 50, no 3, p. 1110-1138Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_23_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:23:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_23_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This paper considers stability and harmonic analysis of a general class of pulse-modulated systems. The systems are modeled using the dynamic phasor model, which explores the cyclic nature of the modulation functions by representing the system state as a Fourier series expansion defined over a moving time window. The contribution of the paper is to show that a special type of periodic Lyapunov function can be used to analyze the system and that the analysis conditions become tractable for computation after truncation. The approach provides a trade-off between complexity and accuracy that includes standard state space averaged models as a special case. The paper also shows how the dynamic phasor model can be used to derive a frequency domain input-to-state map which is analogous to the harmonic transfer function.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:23:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 25. Dynamic phasor analysis of pulse-modulated systems Almér, Stefan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_24_j_idt591",{id:"formSmash:items:resultList:24:j_idt591",widgetVar:"widget_formSmash_items_resultList_24_j_idt591",onLabel:"Almér, Stefan ",offLabel:"Almér, Stefan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_24_j_idt594",{id:"formSmash:items:resultList:24:j_idt594",widgetVar:"widget_formSmash_items_resultList_24_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:24:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Jönsson, UlfKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:24:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Dynamic phasor analysis of pulse-modulated systems2007In: Proceedings Of The 46th IEEE Conference On Decision And Control, Vols 1-14, 2007, p. 3938-3945Conference paper (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_24_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:24:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_24_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The paper considers stability analysis of a general class of pulse modulated systems in a phasor dynamic framework. The dynamic phasor model exploits the cyclic nature of the modulation functions by representing the system dynamics in terms of a Fourier series expansion defined over a moving time-window. The contribution of the paper is to show that a special type of periodic Lyapunov function can be used to analyze the system and that the analysis conditions become tractable for computation after truncation. The approach provides a trade-off between complexity and accuracy that includes standard state space averaged models as a special case.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:24:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 26. Harmonic analysis of pulse-width modulated systems Almér, Stefan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_25_j_idt591",{id:"formSmash:items:resultList:25:j_idt591",widgetVar:"widget_formSmash_items_resultList_25_j_idt591",onLabel:"Almér, Stefan ",offLabel:"Almér, Stefan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_25_j_idt594",{id:"formSmash:items:resultList:25:j_idt594",widgetVar:"widget_formSmash_items_resultList_25_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:25:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Jönsson, UlfKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:25:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Harmonic analysis of pulse-width modulated systems2009In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 45, no 4, p. 851-862Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_25_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:25:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_25_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The paper considers the so-called dynamic phasor model as a basis for harmonic analysis of a class switching systems. The analysis covers both periodically switched systems and non-periodic systems where the switching is controlled by feedback. The dynamic phasor model is a powerful tool for exploring cyclic properties of dynamic systems. It is shown that there is a connection between the dynamic phasor model and the harmonic transfer function of a linear time periodic system and this connection is used to extend the notion of harmonic transfer function to describe periodic solutions of non-periodic systems.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:25:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 27. Harmonic Lyapunov functions in the analysis of periodically switched systems Almér, Stefan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_26_j_idt591",{id:"formSmash:items:resultList:26:j_idt591",widgetVar:"widget_formSmash_items_resultList_26_j_idt591",onLabel:"Almér, Stefan ",offLabel:"Almér, Stefan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_26_j_idt594",{id:"formSmash:items:resultList:26:j_idt594",widgetVar:"widget_formSmash_items_resultList_26_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:26:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Jönsson, UlfKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:26:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Harmonic Lyapunov functions in the analysis of periodically switched systems2006In: PROCEEDINGS OF THE 45TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-14, 2006, p. 2759-2764Conference paper (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_26_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:26:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_26_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The dynamic phasor model of a time-periodic system is used to derive a stability test involving a harmonic Lyapunov function. This reveals a new interpretation of the harmonic Lyapunov function with an appealing time-domain representation. Most importantly, it indicates that the ideas behind the harmonic Lyapunov equation can be generalized to include cyclic switching systems that have different pulse form in each period.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:26:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 28. Stability analysis of a class of PWM systems Almér, Stefan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_27_j_idt591",{id:"formSmash:items:resultList:27:j_idt591",widgetVar:"widget_formSmash_items_resultList_27_j_idt591",onLabel:"Almér, Stefan ",offLabel:"Almér, Stefan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_27_j_idt594",{id:"formSmash:items:resultList:27:j_idt594",widgetVar:"widget_formSmash_items_resultList_27_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:27:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Jönsson, UlfKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.Kao, Chung-YaoUniv Melbourne, Dept Elect & Elect Engn.Mari, JorgeGE Global Res, Elect Energy Syst.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:27:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Stability analysis of a class of PWM systems2007In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 52, no 6, p. 1072-1078Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_27_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:27:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_27_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This note considers stability analysis of a class of pulsewidth modulated (PWM) systems that incorporates several different switched mode dc-de- converters. The systems of the class typically have periodic solutions. A sampled data model is developed and used to prove stability of these solutions. Conditions for global and local exponential stability are derived using quadratic and piecewise quadratic Lyapunov functions. The state space is partitioned and the stability conditions are verified by checking a set of coupled linear matrix inequalities (LMIs).

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:27:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 29. Dynamic phasor analysis of a class of PWM systems Almér, Stefan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_28_j_idt591",{id:"formSmash:items:resultList:28:j_idt591",widgetVar:"widget_formSmash_items_resultList_28_j_idt591",onLabel:"Almér, Stefan ",offLabel:"Almér, Stefan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_28_j_idt594",{id:"formSmash:items:resultList:28:j_idt594",widgetVar:"widget_formSmash_items_resultList_28_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:28:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Jönsson, Ulf T.KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:28:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Dynamic phasor analysis of a class of PWM systems2015In: 2007 European Control Conference, ECC 2007, 2015, p. 1940-1947Conference paper (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_28_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:28:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_28_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The paper makes use of the so-called dynamic phasor model for stability and performance analysis of a class of PWM systems. The dynamic phasor model allows for the state to be represented in the frequency domain where a harmonic Lyapunov function is defined. The analysis covers both periodically switched systems and non-periodic systems where the switching is controlled by feedback.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:28:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 30. Dynamic Phasor Analysis of Periodic Systems Almér, Stefan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_29_j_idt591",{id:"formSmash:items:resultList:29:j_idt591",widgetVar:"widget_formSmash_items_resultList_29_j_idt591",onLabel:"Almér, Stefan ",offLabel:"Almér, Stefan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_29_j_idt594",{id:"formSmash:items:resultList:29:j_idt594",widgetVar:"widget_formSmash_items_resultList_29_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:29:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Jönsson, Ulf T.KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:29:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Dynamic Phasor Analysis of Periodic Systems2009In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 54, no 8, p. 2007-2012Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_29_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:29:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_29_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The paper considers stability analysis of linear time-periodic (LTP) systems based on the dynamic phasor model (DPM). The DPM exploits the periodicity of the system by expanding the system state in a Fourier series over a moving time window. This results in an L-2-equivalent representation in terms of an infinite-dimensional LTI system which describes the evolution of time varying Fourier coefficients. To prove stability, we consider quadratic time-periodic Lyapunov candidates. Using the DPM, the corresponding time-periodic Lyapunov inequality can be stated as a finite dimensional inequality and the Lyapunov function can be found by solving a linear matrix inequality.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:29:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 31. Optimization of Production Scheduling in the Dairy Industry Alvfors, Oskar PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_30_j_idt591",{id:"formSmash:items:resultList:30:j_idt591",widgetVar:"widget_formSmash_items_resultList_30_j_idt591",onLabel:"Alvfors, Oskar ",offLabel:"Alvfors, Oskar ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_30_j_idt594",{id:"formSmash:items:resultList:30:j_idt594",widgetVar:"widget_formSmash_items_resultList_30_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:30:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Björelind, FredrikKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:30:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Optimization of Production Scheduling in the Dairy Industry2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_30_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:30:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_30_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This thesis presents a case study of mathematical production scheduling optimization applied on Arla Foods AB’s production of dairy products. The scheduling was performed as a possible remedy for problems caused by overcrowded finished goods warehouse. Based on the scheduling, conclusions were made on whether the existing two-shift production is sufficient or if an additional night shift should be introduced. In parallel, an empirical and theoretical analysis on the perceived effects of night shift work on employees was conducted.

For the optimization, mixed integer programming was used to model the production context through a discrete time scheduling lot-sizing model developed in this thesis. The model developed and implemented on Arla Foods AB contributes to the research field through its feature of relatively low complexity enabling scheduling of extensive production systems when applied in industrial contexts where products may be categorized.

The thesis concludes that mathematical production scheduling can solve Arla Foods AB’s production problematics and suggests reallocation of the existing shifts for the purpose of reduced costs and acceptable warehouse levels. This reallocation would incur production during inconvenient hours whereas management remedies reducing negative effects of night shift work are identified.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:30:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_30_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:30:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_30_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:30:j_idt854:0:fullText"});}); 32. Shift Design and Driver Scheduling Problem Alvianto Priyanto, Criss PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_31_j_idt591",{id:"formSmash:items:resultList:31:j_idt591",widgetVar:"widget_formSmash_items_resultList_31_j_idt591",onLabel:"Alvianto Priyanto, Criss ",offLabel:"Alvianto Priyanto, Criss ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:31:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:31:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Shift Design and Driver Scheduling Problem2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_31_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:31:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_31_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Scheduling problem and shift design problems are well known NP-hard problems within the optimization area. Often time, the two problems are studied individually. In this thesis however, we are looking at the combination of both problems. More specifically, the aim of this thesis is to suggest an optimal scheduling policy given that there are no predefined shifts to begin with. The duration of a shift, along with the start and end time may vary. Thus we have proposed to split the problem into two sub-problems: weekly scheduling problem and daily scheduling problem. As there are no exact solution methods that are feasible, two meta-heuristics method has been employed to solve the sub-problems: Simulated Annealing (SA) and Genetic Algorithm (GA). We have provided proofs of concepts for both methods as well as explored the scalability. This is especially important as the number of employee is expected to grow significantly throughout the year. The results obtained has shown to be promising and can be built upon for further capabilities.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:31:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_31_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:31:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_31_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:31:j_idt854:0:fullText"});}); 33. Improved Differential Diagnostics Using Methods in Machine Learning and Regression Andblom, Mikael PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_32_j_idt591",{id:"formSmash:items:resultList:32:j_idt591",widgetVar:"widget_formSmash_items_resultList_32_j_idt591",onLabel:"Andblom, Mikael ",offLabel:"Andblom, Mikael ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:32:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:32:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Improved Differential Diagnostics Using Methods in Machine Learning and Regression2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_32_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:32:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_32_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); There is a desire both from the patient and the society to have eﬃcient tools for diﬀerential diagnostics. Mathematical relationships between diseases and observable consequences are deﬁned in the thesis. Speciﬁcally artiﬁcial neural networks are considered in the modeling of the doctor’s methodology. To suggest further lab tests or symptoms to look for the network is inverted by looking at a minimization problem where the objective function gradient can be analytically calculated. Due to diﬃculties in obtaining real life medical data a program was constructed to generate artiﬁcial patient data sets. These data sets will be used to establish proof of concepts. Some data set quality measures are deﬁned and used to model the network accuracy and training time. It is then estimated that a problem with 4000 diagnoses and 20 000 observable consequences would require 200 000 patients to obtain a classiﬁcation accuracy of 99% with a training time of 50 hours depending on the computational power. Overall the solution strategy seems promising but studies on real life data is required for deﬁnitive answers.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:32:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_32_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:32:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_32_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:32:j_idt854:0:fullText"});}); 34. Curve Fitting Using Calculus in Normed Spaces Andersson, Eva PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_33_j_idt591",{id:"formSmash:items:resultList:33:j_idt591",widgetVar:"widget_formSmash_items_resultList_33_j_idt591",onLabel:"Andersson, Eva ",offLabel:"Andersson, Eva ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_33_j_idt594",{id:"formSmash:items:resultList:33:j_idt594",widgetVar:"widget_formSmash_items_resultList_33_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:33:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Sandström, MarleneKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.Sjöholm, OttoKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.Kjaerboe, FilippaKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:33:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Curve Fitting Using Calculus in Normed Spaces2011Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_33_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:33:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_33_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Curve fitting is used in a variety of fields, especially in physics, mathematics and economics.

The method is often used to smooth noisy data and for doing path planning. In this bachelor

thesis calculus of variations will be used to derive a formula for finding an optimal curve to fit a

set of data points. We evaluate a cost function (defined on the set of all curves

f on the interval

[

a; b]) given by F(f) =

R

b

a

(f00(x))2dx +

P

n

i

=1(f(xi) yi)2. The integral term represents the

smoothness of the curve, the interpolation error is given by the summation term and

> 0 is

defined as the interpolation parameter. An ideal curve minimizes the interpolation error and

is relatively smooth. This is problematic since a smooth function generally has a large interpolation

error when doing curve fitting, and therefore the interpolation parameter

is needed

to decide how much consideration should be given to each attribute. For the cost function

F

a larger value of

decreases the interpolation error of the curve. The analytical calculations

performed made it possible to construct a

Matlab program, that could be used to solve the

minimization problem. In the result part some examples are presented for different values of

.

The conclusion is that a larger value of the interpolation parameter

is generally needed when

using more data points and if the points are closely placed on the x-axis. Further on, a method

called Ordinary Cross Validation (OCV) is evaluated to find an optimal value of

. This method

gave good results, except for the case when the points could almost be fitted with a straight line.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:33:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_33_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:33:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_33_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:33:j_idt854:0:fullText"});}); 35. Solving the Train Timetabling Problem by using Rapid Branching Andersson, Jerker PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_34_j_idt591",{id:"formSmash:items:resultList:34:j_idt591",widgetVar:"widget_formSmash_items_resultList_34_j_idt591",onLabel:"Andersson, Jerker ",offLabel:"Andersson, Jerker ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:34:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:34:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Solving the Train Timetabling Problem by using Rapid Branching2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_34_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:34:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_34_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The topic of this thesis is the implementation of rapid branching to find an integer solution for the train timetabling problem. The techniques that rapid branching are based on are presented. The important aspect of rapid branching are discussed and then the algorithm is applied to some artificial problems. It is shown that rapid branching can be both faster and slower than a standard integer solver depending on the problem instance. For the most realistic set of the examined instances, rapid branching turned out to be faster than the standard integer solver and produce satisficingly high quality solutions.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:34:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_34_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:34:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_34_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:34:j_idt854:0:fullText"});}); 36. Adaptive node distribution for on-line trajectory planning Anisi, David A. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_35_j_idt591",{id:"formSmash:items:resultList:35:j_idt591",widgetVar:"widget_formSmash_items_resultList_35_j_idt591",onLabel:"Anisi, David A. ",offLabel:"Anisi, David A. ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:35:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:35:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Adaptive node distribution for on-line trajectory planning2006In: ICAS-Secretariat - 25th Congress of the International Council of the Aeronautical Sciences 2006, Curran Associates, Inc., 2006, p. 3150-3157Conference paper (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_35_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:35:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_35_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Direct methods for trajectory optimization are traditionally based on a priori temporal dis- cretization and collocation methods. In this work, the problem of node distribution is for- mulated as an optimization problem, which is to be included in the underlying non-linear mathematical programming problem (NLP). The benefits of utilizing the suggested method for on-line trajectory optimization are illustrated by a missile guidance example.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:35:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 37. Adaptive Node Distribution for Online Trajectory Planning Anisi, David A. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_36_j_idt591",{id:"formSmash:items:resultList:36:j_idt591",widgetVar:"widget_formSmash_items_resultList_36_j_idt591",onLabel:"Anisi, David A. ",offLabel:"Anisi, David A. ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:36:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:36:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Adaptive Node Distribution for Online Trajectory PlanningManuscript (Other academic)38. On Cooperative Surveillance, Online Trajectory Planning and Observer Based Control Anisi, David A. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_37_j_idt591",{id:"formSmash:items:resultList:37:j_idt591",widgetVar:"widget_formSmash_items_resultList_37_j_idt591",onLabel:"Anisi, David A. ",offLabel:"Anisi, David A. ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:37:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:37:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); On Cooperative Surveillance, Online Trajectory Planning and Observer Based Control2009Doctoral thesis, comprehensive summary (Other academic)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_37_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:37:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_37_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The main body of this thesis consists of six appended papers. In the first two, different cooperative surveillance problems are considered. The second two consider different aspects of the trajectory planning problem, while the last two deal with observer design for mobile robotic and Euler-Lagrange systems respectively.In Papers A and B, a combinatorial optimization based framework to cooperative surveillance missions using multiple Unmanned Ground Vehicles (UGVs) is proposed. In particular, Paper A considers the the Minimum Time UGV Surveillance Problem (MTUSP) while Paper B treats the Connectivity Constrained UGV Surveillance Problem (CUSP). The minimum time formulation is the following. Given a set of surveillance UGVs and a polyhedral area, find waypoint-paths for all UGVs such that every point of the area is visible from a point on a waypoint-path and such that the time for executing the search in parallel is minimized. The connectivity constrained formulation extends the MTUSP by additionally requiring the induced information graph to be kept recurrently connected at the time instants when the UGVs perform the surveillance mission. In these two papers, the NP-hardness of both these problems are shown and decomposition techniques are proposed that allow us to find an approximative solution efficiently in an algorithmic manner.Paper C addresses the problem of designing a real time, high performance trajectory planner for an aerial vehicle that uses information about terrain and enemy threats, to fly low and avoid radar exposure on the way to a given target. The high-level framework augments Receding Horizon Control (RHC) with a graph based terminal cost that captures the global characteristics of the environment. An important issue with RHC is to make sure that the greedy, short term optimization does not lead to long term problems, which in our case boils down to two things: not getting into situations where a collision is unavoidable, and making sure that the destination is actually reached. Hence, the main contribution of this paper is to present a trajectory planner with provable safety and task completion properties. Direct methods for trajectory optimization are traditionally based on a priori temporal discretization and collocation methods. In Paper D, the problem of adaptive node distribution is formulated as a constrained optimization problem, which is to be included in the underlying nonlinear mathematical programming problem. The benefits of utilizing the suggested method for online trajectory optimization are illustrated by a missile guidance example.In Paper E, the problem of active observer design for an important class of non-uniformly observable systems, namely mobile robotic systems, is considered. The set of feasible configurations and the set of output flow equivalent states are defined. It is shown that the inter-relation between these two sets may serve as the basis for design of active observers. The proposed observer design methodology is illustrated by considering a unicycle robot model, equipped with a set of range-measuring sensors. Finally, in Paper F, a geometrically intrinsic observer for Euler-Lagrange systems is defined and analyzed. This observer is a generalization of the observer proposed by Aghannan and Rouchon. Their contractivity result is reproduced and complemented by a proof that the region of contraction is infinitely thin. Moreover, assuming a priori bounds on the velocities, convergence of the observer is shown by means of Lyapunov's direct method in the case of configuration manifolds with constant curvature.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:37:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)FULLTEXT01$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_37_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:37:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_37_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:37:j_idt854:0:fullText"});}); 39. Riemannian Observers for Euler-Lagrange Systems Anisi, David A. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_38_j_idt591",{id:"formSmash:items:resultList:38:j_idt591",widgetVar:"widget_formSmash_items_resultList_38_j_idt591",onLabel:"Anisi, David A. ",offLabel:"Anisi, David A. ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_38_j_idt594",{id:"formSmash:items:resultList:38:j_idt594",widgetVar:"widget_formSmash_items_resultList_38_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:38:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Hamberg, JohanPrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:38:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Riemannian Observers for Euler-Lagrange Systems2005In: Proceedings of the 16th IFAC World Congress: Prague, Czech Republic, July 3-8, 2005, 2005, p. 115-120Conference paper (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_38_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:38:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_38_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); In this paper, a geometrically intrinsic observer for Euler-Lagrange systems is defined and analysed. This observer is an generalization of the observer recently proposed by Aghannan and Rouchon. Their contractivity result is reproduced and complemented by a proof that the region of contractivity is infinitely thin. However, assuming a priori bounds on the velocities, convergence of the observer is shown by means of Lyapunov's direct method in the case of configuration manifolds with constant curvature. The convergence properties of the observer are illustrated by an example where the configuration manifold is the three-dimensional sphere, S

_{3}.PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:38:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 40. Active Observers for Mobile Robotic Systems Anisi, David A. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_39_j_idt591",{id:"formSmash:items:resultList:39:j_idt591",widgetVar:"widget_formSmash_items_resultList_39_j_idt591",onLabel:"Anisi, David A. ",offLabel:"Anisi, David A. ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_39_j_idt594",{id:"formSmash:items:resultList:39:j_idt594",widgetVar:"widget_formSmash_items_resultList_39_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:39:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Hu, XiaomingKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:39:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Active Observers for Mobile Robotic SystemsManuscript (Other academic)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_39_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:39:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_39_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); An important class of non-uniformly observable systems come from applications in mobile robotics. In this paper, the problem of active observer design for such systems is considered. The set of feasible configurations and the set of output flow equivalent states is defined. It is shown that the inter-relation between these two sets serves as the basis for design of active observers. The proposed observer design method is illustrated by considering a unicycle robot model, equipped with a set of range-measuring sensors.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:39:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 41. Minimum time multi-UGV surveillance Anisi, David A. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_40_j_idt591",{id:"formSmash:items:resultList:40:j_idt591",widgetVar:"widget_formSmash_items_resultList_40_j_idt591",onLabel:"Anisi, David A. ",offLabel:"Anisi, David A. ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_40_j_idt594",{id:"formSmash:items:resultList:40:j_idt594",widgetVar:"widget_formSmash_items_resultList_40_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:40:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Ögren, PetterPrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:40:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Minimum time multi-UGV surveillance2008In: OPTIMIZATION AND COOPERATIVE CONTROL STRATEGIES / [ed] Hirsch MJ; Commander CW; Pardalos PM; Murphey R, Berlin: Springer Verlag , 2008, p. 31-45Conference paper (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_40_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:40:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_40_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This paper addresses the problem of concurrent task- and path planning for a number of surveillance Unmanned Ground Vehicles (UGVs) such that a user defined area of interest is covered by the UGVs' sensors in minimum time. We first formulate the problem, and show that it is in fact a generalization of the Multiple Traveling Salesmen Problem (MTSP), which is known to be NP-hard. We then propose a solution that decomposes the problem into three subproblems. The first is to find a maximal convex covering of the search area. Most results on static coverage use disjoint partitions of the search area, e.g. triangulation, to convert the continuous sensor positioning problem into a discrete one. However, by a simple example, we show that a highly overlapping set of maximal convex sets is better suited for minimum time coverage. The second subproblem is a combinatorial assignment and ordering of the sets in the cover. Since Tabu search algorithms are known to perform well on various routing problems, we use it as a part of our proposed solution. Finally, the third subproblem utilizes a particular shortest path sub-routine in order to find the vehicle paths, and calculate the overall objective function used in the Tabu search. The proposed algorithm is illustrated by a number of simulation examples.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:40:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 42. Cooperative Minimum Time Surveillance With Multiple Ground Vehicles Anisi, David A.et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_41_j_idt594",{id:"formSmash:items:resultList:41:j_idt594",widgetVar:"widget_formSmash_items_resultList_41_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:41:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Ögren, PetterSwedish Defence Research Agency (FOI), Sweden.Hu, XiaomingKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:41:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Cooperative Minimum Time Surveillance With Multiple Ground Vehicles2010In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 55, no 12, p. 2679-2691Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_41_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:41:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_41_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); In this paper, we formulate and solve two different minimum time problems related to unmanned ground vehicle (UGV) surveillance. The first problem is the following. Given a set of surveillance UGVs and a polyhedral area, find waypoint-paths for all UGVs such that every point of the area is visible from a point on a path and such that the time for executing the search in parallel is minimized. Here, the sensors' field of view are assumed to have a limited coverage range and be occluded by the obstacles. The second problem extends the first by additionally requiring the induced information graph to be connected at the time instants when the UGVs perform the surveillance mission, i.e., when they gather and transmit sensor data. In the context of the second problem, we also introduce and utilize the notion of recurrent connectivity, which is a significantly more flexible connectivity constraint than, e.g., the 1-hop connectivity constraints and use it to discuss consensus filter convergence for the group of UGVs.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:41:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 43. Cooperative Surveillance Missions with Multiple Unmanned Ground Vehicles (UGVs) Anisi, David A.et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_42_j_idt594",{id:"formSmash:items:resultList:42:j_idt594",widgetVar:"widget_formSmash_items_resultList_42_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:42:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Ögren, PetterKTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.Hu, XiaomingKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.Lindskog, TheresePrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:42:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Cooperative Surveillance Missions with Multiple Unmanned Ground Vehicles (UGVs)2008In: 47TH IEEE CONFERENCE ON DECISION AND CONTROL, 2008 (CDC 2008), 2008, p. 2444-2449Conference paper (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_42_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:42:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_42_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This paper proposes an optimization based approach to multi-UGV surveillance. In particular, we formulate both the minimum time- and connectivity constrained surveillance problems, show NP-hardness of them and propose decomposition techniques that allow us to solve them efficiently in an algorithmic manner. The minimum time formulation is the following. Given a set of surveillance UGVs and a polyhedral area, find waypoint-paths for all UGVs such that every point of the area is visible from a point on a path and such that the time for executing the search in parallel is minimized. Here, the sensor's field of view are assumed to be occluded by the obstacles and limited by a maximal sensor range. The connectivity constrained formulation extends the first by additionally requiring that the information graph induced by the sensors is connected at the time instants when the UGVs stop to perform the surveillance task. The second formulation is relevant to situation when mutual visibility is needed either to transmit the sensor data being gathered, or to protect the team from hostile persons trying to approach the stationary UGVs.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:42:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 44. Safe receding horizon control of an aerial vehicle Anisi, David A. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_43_j_idt591",{id:"formSmash:items:resultList:43:j_idt591",widgetVar:"widget_formSmash_items_resultList_43_j_idt591",onLabel:"Anisi, David A. ",offLabel:"Anisi, David A. ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_43_j_idt594",{id:"formSmash:items:resultList:43:j_idt594",widgetVar:"widget_formSmash_items_resultList_43_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:43:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Ögren, PetterDepartment of Autonomous Systems Swedish Defence Research Agency.Robinson, John W. C.Department of Autonomous Systems Swedish Defence Research Agency.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:43:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Safe receding horizon control of an aerial vehicle2006In: PROCEEDINGS OF THE 45TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-14, IEEE , 2006, p. 57-62Conference paper (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_43_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:43:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_43_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This paper addresses the problem of designing a real time high performance controller and trajectory generator for air vehicles. The control objective is to use information about terrain and enemy threats to fly low and avoid radar exposure on the way to a given target. The proposed algorithm builds on the well known approach of Receding Horizon Control (RHC) combined with a terminal cost, calculated from a graph representation of the environment. Using a novel safety maneuver, and under an assumption on the maximal terrain inclination, we are able to prove safety as well as task completion. The safety maneuver is incorporated in the short term optimization, which is performed using Nonlinear Programming (NLP). Some key characteristics of the trajectory planner are highlighted through simulations.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:43:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 45. Online Trajectory Planning for Aerial Vehicle Anisi, David PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_44_j_idt591",{id:"formSmash:items:resultList:44:j_idt591",widgetVar:"widget_formSmash_items_resultList_44_j_idt591",onLabel:"Anisi, David ",offLabel:"Anisi, David ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_44_j_idt594",{id:"formSmash:items:resultList:44:j_idt594",widgetVar:"widget_formSmash_items_resultList_44_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:44:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Robinson, John W.C.Dept. of Autonomous Systems, Swedish Defence Research Agency (FOI), Stockholm, Sweden.Ögren, PetterDept. of Autonomous Systems, Swedish Defence Research Agency (FOI), Stockholm, Sweden.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:44:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Online Trajectory Planning for Aerial Vehicle: A Safe Approach with Guaranteed Task CompletionManuscript (Other academic)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_44_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:44:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_44_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); On-line trajectory optimization in three dimensional space is the main topic of the paper at hand. The high-level framework augments on-line receding horizon control with an off-line computed terminal cost that captures the global characteristics of the environment, as well as any possible mission objectives. The first part of the paper is devoted to the single vehicle case while the second part considers the problem of simultaneous arrival of multiple aerial vehicles. The main contribution of the first part is two-fold. Firstly, by augmenting a so called safety maneuver at the end of the planned trajectory, this paper extends previous results by addressing provable safety properties in a 3D setting. Secondly, assuming initial feasibility, the planning method presented is shown to have finite time task completion. Moreover, a quantitative comparison between the two competing objectives of optimality and computational tractability is made. Finally, some other key characteristics of the trajectory planner, such as ability to minimize threat exposure and robustness, are highlighted through simulations. As for the simultaneous arrival problem considered in the second part, by using a time-scale separation principle, we are able to adopt standard Laplacian control to a consensus problem which is neither unconstrained, nor first order.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:44:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 46. On-line Trajectory planning for aerial vehicles Anisi, David PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_45_j_idt591",{id:"formSmash:items:resultList:45:j_idt591",widgetVar:"widget_formSmash_items_resultList_45_j_idt591",onLabel:"Anisi, David ",offLabel:"Anisi, David ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_45_j_idt594",{id:"formSmash:items:resultList:45:j_idt594",widgetVar:"widget_formSmash_items_resultList_45_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:45:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Robinson, John W.C.Swedish Defence Research Agency (FOI), Department of Aeronautics .Ögren, PetterSwedish Defence Research Agency (FOI).PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:45:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); On-line Trajectory planning for aerial vehicles: a safe approach with guaranteed task completion2006In: Collection of Technical Papers: AIAA Guidance, Navigation, and Control Conference 2006, 2006, p. 914-938Conference paper (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_45_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:45:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_45_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); On-line trajectory optimization in three dimensional space is the main topic of the paper at hand. The high-level framework augments on-line receding horizon control with an off-line computed terminal cost that captures the global characteristics of the environment, as well as any possible mission objectives. The first part of the paper is devoted to the single vehicle case while the second part considers the problem of simultaneous arrival of multiple aerial vehicles. The main contribution of the first part is two-fold. Firstly, by augmenting a so called safety maneuver at the end of the planned trajectory, this paper extends previous results by addressing provable safety properties in a 3 D setting. Secondly, assuming initial feasibility, the planning method presented is shown to have finite time task completion. Moreover, a quantitative comparison between the two competing objectives of optimality and computational tractability is made. Finally, some other key characteristics of the trajectory planner, such as ability to minimize threat exposure and robustness, are highlighted through simulations. As for the simultaneous arrival problem considered in the second part, by using a time-scale separation principle, we are able to adopt standard Laplacian control to a consensus problem which is neither unconstrained, nor first order.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:45:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 47. OptimalSpeed Controller for a Heavy-Duty Vehicle in the Presence of SurroundingTraffic Arnoldsson, Jakob PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_46_j_idt591",{id:"formSmash:items:resultList:46:j_idt591",widgetVar:"widget_formSmash_items_resultList_46_j_idt591",onLabel:"Arnoldsson, Jakob ",offLabel:"Arnoldsson, Jakob ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:46:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:46:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); OptimalSpeed Controller for a Heavy-Duty Vehicle in the Presence of SurroundingTraffic2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_46_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:46:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_46_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This thesis has explored the concept of an intelligent fuel-efficient speed controller for a heavy-duty vehicle, given that it is limited by a preceding vehicle. A Model Predictive Controller (MPC) has been developed together with a PI-controller as a reference controller. The MPC based controller utilizes future information about the traffic conditions such as the road topography, speed restrictions and velocity of the preceding vehicle to make fuel-efficient decisions. Simulations have been made for a so called Deterministic case, meaning that the MPC is given full information about the future traffic conditions, and a Stochastic case where the future velocity of the preceding vehicle has to be predicted. For the first case, regenerative braking as well as a simple distance dependent model for the air drag coefficient are included. For the second case three prediction models are created: two rule based models (constant velocity, constant acceleration) and one learning algorithm, a so called Nonlinear Auto Regressive eXogenous (NARX) network.

Computer simulations have been performed, on both created test cases as well as on logged data from a Scania vehicle. The developed models are finally evaluated on the test cases for both varying masses and allowed deviations from the preceding vehicle. The simulations show on a potential for fuel savings with the MPC based speed controllers both for the deterministic as well as the stochastic case.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:46:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_46_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:46:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_46_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:46:j_idt854:0:fullText"});}); 48. Optimal löptidsallokering av bostadslån Aronsson, Petter PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_47_j_idt591",{id:"formSmash:items:resultList:47:j_idt591",widgetVar:"widget_formSmash_items_resultList_47_j_idt591",onLabel:"Aronsson, Petter ",offLabel:"Aronsson, Petter ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_47_j_idt594",{id:"formSmash:items:resultList:47:j_idt594",widgetVar:"widget_formSmash_items_resultList_47_j_idt594",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:47:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Ronneback Thomson, JoachimKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:47:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Optimal löptidsallokering av bostadslån2014Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_47_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:47:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_47_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This Bachelor’s thesis introduces a dynamic method for allocation of adjustable-rate mortgages which can be used to reduce a growing social problem. The Swedish household’s debt has steadily increased and the primary cause is mortgages loans, used to fund the purchase of a real property. Because of a period of rising home prices, Swedes are mortgaged more than ever [1]. If interest rates go up there is an increased risk of not managing the interest charge which is the greatest expense for many households.

However, there is an absence in the debate of the importance of efficient and safe mortgages. By means of the introduced dynamic method, this thesis optimizes the allocation of adjustable-rate mortgages, using both historical and future cases. In the forecasting case, expected interest charge and risk are being minimized. More specifically, the method consider three levels of risk which all values expected interest charge and risk differently. Further, the goal is to apply the dynamic method for decision support in reality and also commercialize as a business idea.

Modeling mortgage as a network flow is essential for the dynamic method. This way enables analysis of mortgages during a period of time which is necessary for determining an optimal allocation of adjustable-rate mortgages. The result from the historical case shows that shorter adjustment periods have been more favorable. Though, to an extent lower than expected – only during seven out of the last seventeen years. In addition, the results from the forecasting case indicate that it is advantageous to choose longer adjustment periods. Finally introduces a business model for the startup company, Looptime AB, of which business idea is toadminister mortgages for households, residents’ associations and non-financial companies.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:47:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 49. Data gathering and analysis in gaming using Tobii Eye Tracking Aukrust Avemo, Jonas PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_48_j_idt591",{id:"formSmash:items:resultList:48:j_idt591",widgetVar:"widget_formSmash_items_resultList_48_j_idt591",onLabel:"Aukrust Avemo, Jonas ",offLabel:"Aukrust Avemo, Jonas ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:48:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:48:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Data gathering and analysis in gaming using Tobii Eye Tracking2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_48_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:48:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_48_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); E-sports is growing and the price pools in e-sports tournaments are increasing, Valves video game DotA 2 is one of the bigger e-sports. As professional gamers train to increase their skill, new tools to help the training might become very important. Eye tracking can give an extra training dimension for the gamer. The aim of this master thesis is to develop a Visual Attention Index for DotA 2, that is, a number that reflects the player’s visual attention during a game. Interviews with gamers combined with data collection from gamers with eye trackers and statistical methods were used to find relevant metrics to use in the work. The results show that linear regression did not work very well on the data set, however, since there were a low number of test persons, further data collection and testing needs to be done before any statistically significant conclusions can be drawn. Support Vector Machines (SVM) was also used and turned out to be an effective way of separating better players from less good players. A new SVM method, based on linear programming, was also tested and found to be efficient and easy to apply on the given data set.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:48:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_48_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:48:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_48_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:48:j_idt854:0:fullText"});}); 50. Divergence-based spectral approximation with degree constraint as a concave optimization problem Avventi, Enrico PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_49_j_idt591",{id:"formSmash:items:resultList:49:j_idt591",widgetVar:"widget_formSmash_items_resultList_49_j_idt591",onLabel:"Avventi, Enrico ",offLabel:"Avventi, Enrico ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:49:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:49:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Divergence-based spectral approximation with degree constraint as a concave optimization problemManuscript (preprint) (Other academic)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_49_j_idt629_0_j_idt630",{id:"formSmash:items:resultList:49:j_idt629:0:j_idt630",widgetVar:"widget_formSmash_items_resultList_49_j_idt629_0_j_idt630",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The Kullback-Leibler pseudo-distance, or divergence, can be used as a criterion for spectral approximation. Unfortunately this criterion is not convex over the most general classes of rational spectra. In this work it will be shown that divergence minimization is equivalent to a costrained entropy minimization problem, whose concave structure can be exploited in order to guarantee global convergence in the most general case.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:49:j_idt629:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Download full text (pdf)fulltext$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_items_resultList_49_j_idt854_0_j_idt857",{id:"formSmash:items:resultList:49:j_idt854:0:j_idt857",widgetVar:"widget_formSmash_items_resultList_49_j_idt854_0_j_idt857",showEffect:"fade",hideEffect:"fade",target:"formSmash:items:resultList:49:j_idt854:0:fullText"});});

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