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  • 1.
    Alam, Assad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Asplund, Fredrik
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Behere, Sagar
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Björk, Mattias
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Garcia Alonso, Liliana
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Khaksari, Farzad
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Khan, Altamash
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Kjellberg, Joakim
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Liang, Kuo-Yun
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Lyberger, Rickard
    Scania CV AB.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, John-Olof
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Pettersson, Henrik
    Scania CV AB.
    Pettersson, Simon
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Stålklinga, Elin
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Sundman, Dennis
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Zachariah, Dave
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Cooperative driving according to Scoop2011Report (Other academic)
    Abstract [en]

    KTH Royal Institute of Technology and Scania are entering the GCDC 2011 under the name Scoop –Stockholm Cooperative Driving. This paper is an introduction to their team and to the technical approach theyare using in their prototype system for GCDC 2011.

  • 2. Alam, Assad
    et al.
    Besselink, Bart
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Turri, Valerio
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Heavy-Duty Vehicle Platooning for Sustainable Freight Transportation A COOPERATIVE METHOD TO ENHANCE SAFETY AND EFFICIENCY2015In: IEEE CONTROL SYSTEMS MAGAZINE, ISSN 1066-033X, Vol. 35, no 6, p. 34-56Article in journal (Refereed)
    Abstract [en]

    The current system of global trade is largely based on transportation and communication technology from the 20th century. Advances in technology have led to an increasingly interconnected global market and reduced the costs of moving goods, people, and technology around the world [1]. Transportation is crucial to society, and the demand for transportation is strongly linked to economic development. Specifically, road transportation is essential since about 60% of all surface freight transportation (which includes road and rail transport) is done on roads [2]. Despite the important role of road freight transportation in the economy, it is facing serious challenges, such as those posed by increasing fuel prices and the need to reduce greenhouse gas emissions. On the other hand, the integration of information and communication technologies to transportation systems-leading to intelligent transportation systems-enables the development of cooperative methods to enhance the safety and energy efficiency of transportation networks. This article focuses on one such cooperative approach, which is known as platooning. The formation of a group of heavy-duty vehicles (HDVs) at close intervehicular distances, known as a platoon (see Figure 1) increases the fuel efficiency of the group by reducing the overall air drag. The safe operation of such platoons requires the automatic control of the velocity of the platoon vehicles as well as their intervehicular distance. Existing work on platooning has focused on the design of controllers for these longitudinal dynamics, in which simple vehicle models are typically exploited and perfect environmental conditions, such as flat roads, are generally assumed. The broader perspective of how platooning can be effectively exploited in a freight transportation system has received less attention. Moreover, experimental validations of the fuel-saving potential offered by platooning have typically been performed by reproducing the perfect conditions as assumed in the design of the automatic controllers. This article focuses on these two aspects by addressing the following two objectives.

  • 3.
    Alam, Assad
    et al.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Experimental evaluation of decentralized cooperative cruise control for heavy-duty vehicle platooning2015In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 38, p. 11-25Article in journal (Refereed)
    Abstract [en]

    In this paper, we consider the problem of finding decentralized controllers for heavy-duty vehicle (HDV) platooning by establishing empiric results for a qualitative verification of a control design methodology. We present a linear quadratic control framework for the design of a high-level cooperative platooning controller suitable for modern HDVs. A nonlinear low-level dynamical model is utilized, where realistic response delays in certain modes of operation are considered. The controller performance is evaluated through numerical and experimental studies. It is concluded that the proposed controller behaves well in the sense that experiments show that it allows for short time headways to achieve fuel efficiency, without compromising safety. Simulation results indicate that the model mimics real life behavior. Experiment results show that the dynamic behavior of the platooning vehicles depends strongly on the gear switching logic, which is confirmed by the simulation model. Both simulation and experiment results show that the third vehicle never displays a bigger undershoot than its preceding vehicle. The spacing errors stay bounded within 6.8. m in the simulation results and 7.2. m in the experiment results for varying transient responses. Furthermore, a minimum spacing of -0.6. m and -1.9. m during braking is observed in simulations and experiments, respectively. The results indicate that HDV platooning can be conducted at close spacings with standardized sensors and control units that are already present on commercial HDVs today.

  • 4.
    Alam, Assad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.
    Look-Ahead Cruise Control for Heavy Duty Vehicle Platooning2013In: Proceedings of the 16th International IEEE Annual Conference onIntelligent Transportation Systems (ITSC 2013), IEEE conference proceedings, 2013, p. 928-935Conference paper (Refereed)
    Abstract [en]

    Vehicle platooning has become important for thevehicle industry. Yet conclusive results with respect to thefuel reduction possibilities of platooning remain unclear, inparticular when considering constraints imposed by the topography.The focus of this study is to establish whether itis more fuel-efficient to maintain or to split a platoon that isfacing steep uphill and downhill segments. Two commercialcontrollers, an adaptive cruise controller and a look-aheadcruise controller, are evaluated and alternative novel controlstrategies are proposed. The results show that an improvedfuel-efficiency can be obtained by maintaining the platoonthroughout a hill. Hence, a cooperative control strategy basedon preview information is presented, which initiates the changein velocity at a specific point in the road for all vehiclesrather than simultaneously changing the velocity to maintainthe spacing. A fuel reduction of up to 14% can be obtainedover a steep downhill segment and a more subtle benefit of0.7% improvement over an uphill segment with the proposedcontroller, compared to the combination of the commerciallyavailable cruise controller and adaptive cruise controller thatcould be used for platooning. The findings show that it isboth fuel-efficient and desirable in practice to consider previewinformation of the topography in the control strategy.

  • 5.
    Barenthin, Märta
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Jansson, Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Wahlberg, Bo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    A control perspective on optimal input design in system identification2006In: Forever Ljung in System Identification / [ed] Torkel Glad and Gustaf Hendeby, Lund: Studentlitteratur, 2006, p. 197-220Chapter in book (Other academic)
  • 6.
    Besselink, Bart
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Turri, Valerio
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Van De Hoef, Sebastian Hendrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Liang, Kuo-Yun
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Scania CV AB, Sweden.
    Alam, A.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Cyber-Physical Control of Road Freight Transport2016In: Proceedings of the IEEE, ISSN 0018-9219, E-ISSN 1558-2256, Vol. 104, no 5, p. 1128-1141, article id 7437386Article in journal (Refereed)
    Abstract [en]

    Freight transportation is of outmost importance in our society and is continuously increasing. At the same time, transporting goods on roads accounts for about 26% of the total energy consumption and 18% of all greenhouse gas emissions in the European Union. Despite the influence the transportation system has on our energy consumption and the environment, road transportation is mainly done by individual long-haulage trucks with no real-time coordination or global optimization. In this paper, we review how modern information and communication technology supports a cyber-physical transportation system architecture with an integrated logistic system coordinating fleets of trucks traveling together in vehicle platoons. From the reduced air drag, platooning trucks traveling close together can save about 10% of their fuel consumption. Utilizing road grade information and vehicle-to-vehicle communication, a safe and fuel-optimized cooperative look-ahead control strategy is implemented on top of the existing cruise controller. By optimizing the interaction between vehicles and platoons of vehicles, it is shown that significant improvements can be achieved. An integrated transport planning and vehicle routing in the fleet management system allows both small and large fleet owners to benefit from the collaboration. A realistic case study with 200 heavy-duty vehicles performing transportation tasks in Sweden is described. Simulations show overall fuel savings at more than 5% thanks to coordinated platoon planning. It is also illustrated how well the proposed cooperative look-ahead controller for heavy-duty vehicle platoons manages to optimize the velocity profiles of the vehicles over a hilly segment of the considered road network.

  • 7. Eilers, S.
    et al.
    Mårtensson, Jonas
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Pettersson, H.
    Pillado, M.
    Gallegos, D.
    Tobar, M.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Ma, Xiaoliang
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Friedrichs, T.
    Borojeni, S. S.
    Adolfson, M.
    COMPANION-Towards Co-operative Platoon Management of Heavy-Duty Vehicles2015In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, IEEE , 2015, p. 1267-1273Conference paper (Refereed)
    Abstract [en]

    The objective of the EU project COMPANION is to develop co-operative mobility technologies for supervised vehicle platooning, in order to improve fuel efficiency and safety for goods transport. The potential social and environmental benefits inducted by heavy-duty vehicle platoons have been largely proven. However, until now, the creation, coordination, and operation of such platoons have been mostly neglected. In addition, the regulation and standardization of coordinated platooning, together with its acceptance by the end-users and the society need further attention and research. In this paper we give an overview over the project and present the architecture of the off-board and onboard platforms of the COMPANION cooperative platoon management system. Furthermore, the consortium reports on the first results of the human factors for platooning, legislative analysis of platooning aspects, clustering and optimization of platooning plans and prediction of congestion due to planned special events. Finally, we present the method of validation of the system via simulation and trials.

  • 8.
    Flärdh, Oscar
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ericsson, Gustav
    AVL MTS, Södertälje, Sweden.
    Klingborg, Erik
    AVL MTS, Södertälje, Sweden.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Optimal Air Path Control During Load Transients on a Spark Ignited Engine With Variable Geometry Turbine and Variable Valve Timing2014In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 22, no 1, p. 83-93Article in journal (Refereed)
    Abstract [en]

    In recent years, the main goal of the automative industry has been to reduce fuel consumption. Downsizing is a promising way to achieve this, which has shown success. Downsized, turbocharged engines suffer from slow transient torque response. This slow response is due to the slow dynamics of the turbocharger. This paper investigates the torque response of a spark ignited engine with variable geometry turbine (VGT) and variable valve timing. Optimal open-loop trajectories for the overlap and the VGT position for a fast transient response are found. This optimization is based on a 1-D simulation model. Based on this optimization, a generic feedback strategy for controlling the VGT is found. This strategy is implemented and evaluated on an engine and shows good performance.

  • 9.
    Flärdh, Oscar
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ericsson, Gustav
    Klingborg, Erik
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Optimal Air Path Control during Load Transients on an SI Engine with VGT and VVTIn: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865Article in journal (Other academic)
    Abstract [en]

    In recent years, the aim to reduce fuel consumption has been the main goal forthe automotive industry. Downsizing is a promising way to achieve this whichhas shown success. Downsized, turbocharged engines do however suffer from slowtransient torque response. This slow response is due to the slow dynamics of theturbocharger. This paper investigates the torque response of an si engine with vvtand vvt. Optimal open-loop trajectories for the overlap and the vgt position for afast transient response are found. This optimization is based on a one-dimensionalsimulation model. Based on this optimization, a generic feedback strategy forcontrolling the vgt is found. This strategy is implemented and evaluated on anengine and shows good performance.

  • 10.
    Flärdh, Oscar
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Analysis of a Quasi-Steady Extension to the Turbine Model in Mean Value Engine Models2010Conference paper (Refereed)
    Abstract [en]

    The aim to reduce fuel consumption and emissions has been targeted by several approaches. One of them is downsizing, where a small engine is equipped with a turbocharger in order to give the same power as a larger engine, but with less fuel consumption. This in turn requires advanced control systems to take full benefit from the downsizing. Recent hardware advancements have enabled the use of variable geometry turbochargers also on SI engines, pushing the control demands further. This paper investigates possible extensions to control oriented mean value engine models for turbocharged SI-engines, focusing on the turbine. Mean value models do not take the pulsating phenomena in the exhaust manifold into account. This is assumed to cause large model errors, especially for the turbine efficiency and turbine power. The main contribution of this paper is to present an investigation of the effects of incorporating pressure pulses in the mean value model, together with an analysis of the effects of the pulsation on the turbine performance maps. An evaluation of the extended mean value model using measurements on a four cylinder SI engine with a variable geometry turbocharger is also presented. The evaluation show little difference between using pressure pulses and mean values. An analysis of the expression for turbine power shows that, when treating the maps quasi-steady, the calculated turbine power is almost the same when using pressure pulsations as when using just the mean pressure ratio. The analysis also indicates that this is due to the fact that the turbine power is an approximately linear function of the turbine pressure ratio.

  • 11.
    Flärdh, Oscar
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Exhaust pressure modeling and control on an si engine with vgt2014In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 25, no 1, p. 26-35Article in journal (Refereed)
    Abstract [en]

    For a turbocharged si engine, the exhaust pressure is of high importance for the gas exchange process as well as for the turbine power. It is therefore important to control the exhaust pressure accurately during load transients. This paper presents and evaluates a nonlinear controller for the exhaust pressure in an si engine equipped with a variable geometry turbine. A mapping from the states, inputs, and disturbances to future outputs is formed, and inverting the input/output relation in this mapping gives a control law. The controller, which can be tuned as a pi controller, utilizes a model for the turbine mass flow capturing the flow characteristics over the operating range. This controller is compared to a linear pi controller and a feedback linearization controller. Evaluation is performed using both simulations and measurements on a real engine, showing the superior behavior of the nonlinear controllers over the linear controller for this problem. Moreover, the presented controller achieves almost as good performance as a feedback linearization controller, but with easier tuning and implementation.

  • 12.
    Flärdh, Oscar
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nonlinear Exhaust Pressure Control of an SI Engine with VGT using Partial Model Inversion2010In: 49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2010, p. 6433-6438Conference paper (Refereed)
    Abstract [en]

    An important target for car manufacturerswhen developing new cars is to reduce fuelconsumption. One approach to this problem is to usea downsized turbocharged engine. To fully utilize thebenefits of the new hardware introduced, good controlsystems are needed. This paper presents a nonlinearcontroller for controlling the exhaust pressure in aSI engine equipped with VGT. A mapping from thestates, inputs and disturbances to future outputs isformed, and inverting the input-output relation inthis mapping gives a control law. An analysis showsthat the controller adapts its gain to the input-outputsensitivity. The controller is evaluated using both simulationsand measurements on a real engine, showingthe benefit of using the nonlinear controller over acorresponding linear controller.

  • 13.
    Gerencser, Laszlo
    et al.
    Computer and Automation Institute of the Hungarian Academy of Sciences, (MTA SZTAKI),.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Identification of ARX systems with non-stationary inputs - asymptotic analysis with application to adaptive input design2009In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 45, no 3, p. 623-633Article in journal (Refereed)
    Abstract [en]

    A key problem in optimal input design is that the solution depends on system parameters to be identified. In this contribution we provide formal results for convergence and asymptotic optimality of an adaptive input design method based on the certainty equivalence principle, i.e. for each time step an optimal input design problem is solved exactly using the present parameter estimate and one sample of this input is applied to the system. The results apply to stable ARX systems with the input restricted to be generated by white noise filtered through a finite impulse response filter, or a binary signal obtained from the latter by a static nonlinearity.

  • 14.
    Gerencser, Laszlo
    et al.
    Computer and Automation Institute of the Hungarian Academy of Sciences, (MTA SZTAKI),.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Adaptive input design for ARX systems2007In: Proceedings of the European Control Conference, Institute of Electrical and Electronics Engineers Inc. , 2007, p. 5707-5714Conference paper (Refereed)
    Abstract [en]

    A key problem in optimal input design is that the solution depends on system parameters to be identified. In this contribution we provide formal results for convergence and asymptotic optimality of an adaptive input design method based on the certainty equivalence principle, i.e. for each time step an optimal input design problem is solved using the present parameter estimate and one sample of this input is applied to the system. The results apply to stable ARX systems with the input restricted to be generated by white noise filtered through an FIR filter, or a binary signal obtained from the latter by a static nonlinearity.

  • 15.
    Henriksson, Manne
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. Scania CV AB, Sweden.
    Flärdh, Oscar
    Scania CV AB.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Optimal Powertrain Control of a Heavy-Duty Vehicle Under Varying Speed Requirements2017Conference paper (Refereed)
    Abstract [en]

    Reducing the fuel consumption is a major issue in the vehicle industry. In this paper, it is done by formulatinga driving mission of a heavy-duty truck as an optimal control problem and solving it using dynamic programming.The vehicle model includes an engine and a gearbox with parameters based on measurements in test cells. The dynamic programming algorithm is solved by considering four specifictypes of transitions: transitions between the same gear, coastingin neutral gear, coasting with a gear engaged with no fuel injection and transitions involving gear changes. Simulations are performed on a driving cycle commonly used for testing distribution type of driving. In order to make sure that the truck does not deviate too much from a normal way of driving, restrictions on maximum and minimum allowed velocities are imposed based on statistics from real traffic data. The simulations show that 12.7% fuel can be saved without increasing the trip time by allowing the truck to engage neutral gear and make small deviations from the reference trajectory.

  • 16.
    Henriksson, Manne
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. Scania CV AB, Sweden.
    Flärdh, Oscar
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Optimal Speed Trajectories Under Variations in the Driving Corridor2017In: IFAC-PapersOnLine, Elsevier, 2017, Vol. 50, p. 12551-12556Conference paper (Refereed)
    Abstract [en]

    The optimal speed trajectory for a heavy-duty truck is calculated using the Pontryagin's maximum principle. The truck motion depends on controllable tractive and braking forces and external forces such as air and rolling resistance and road slope. The velocity of the vehicle is restricted to be within a driving corridor which consists of an upper and a lower boundary. Simulations are performed on data from a test cycle commonly used for testing distribution driving. The data include road slope and a speed reference, from which the driving corridor is created automatically. The simulations include a sensitivity analysis on how changes in the parameters for the driving corridor influence the energy consumption and trip time. For the widest driving corridor tested, 15.8% energy was saved compared to the most narrow corridor without increasing the trip time. Most energy was saved by reducing the losses due to braking and small amounts of energy were saved by reducing the losses due to air resistance. Finally, optimal trajectories with the same trip time derived from different settings on the driving corridor are compared in order to analyse energy efficient driving patterns.

  • 17.
    Henriksson, Manne
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. Scania CV AB, Sweden.
    Flärdh, Oscar
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Optimal Speed Trajectory for a Heavy Duty Truck Under Varying Requirements2016In: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, IEEE, 2016, p. 820-825, article id 7795650Conference paper (Refereed)
    Abstract [en]

    The optimal speed trajectory for a heavy duty truck is calculated by using the Pontryagin’s maximum principle. The truck motion depends on controllable tractive and braking forces and external forces such as air and rolling resistance and road slope. The solution is subject to restrictions such as maximum power and position dependent speed restrictions. The intended application is driving in environments with varying requirements on the velocity due to e.g. legal limits and traffic. In order to limit the vehicle to a speed trajectory that follows the normal traffic flow, data from real truck operation have been analysed and used for setting upper and lower boundaries for the decelerations. To evaluate the solution, simulations have been performed on a segment of a road normally used as a distribution test cycle. Three different policies were compared where the solution adopts to free optimization, optimization following traffic flow and finally cruise control using look-ahead control. Results from the simulations show that fuel consumption and trip time can be reduced simultaneously while following the traffic flow.

  • 18.
    Hjalmarsson, Håkan
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Geometric Approach to Variance Analysis in System Identification2011In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 56, no 5, p. 983-997Article in journal (Refereed)
    Abstract [en]

    This paper addresses the problem of quantifying the model error ("variance-error") in estimates of dynamic systems. It is shown that, under very general conditions, the asymptotic ( in data length) covariance of an estimated system property ( represented by a smooth function of estimated system parameters) can be interpreted in terms of an orthogonal projection of a certain function, associated with the property of interest, onto a subspace determined by the model structure and experimental conditions. The presented geometric approach simplifies structural analysis of the model variance and this is illustrated by analyzing the influence of inputs and sensors on the model accuracy.

  • 19.
    Hjalmarsson, Håkan
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Geometric Approach to Variance Analysis in System Identification: Theory and Nonlinear Systems2007In: PROCEEDINGS OF THE 46TH IEEE CONFERENCE ON DECISION AND CONTRO, 2007, Vol. FrA17.2, p. 5092-5097Conference paper (Refereed)
    Abstract [en]

    This paper addresses the problem of quantifying the model error ("variance-error") in estimates of dynamic systems. It is shown that, under very general conditions, the asymptotic (in data length) covariance of an estimated system property (represented by a smooth function of estimated system parameters) can be interpreted in terms of an orthogonal projection of a certain function gamma, associated with the property of interest, onto a subspace determined by the model structure and experimental conditions. An explicit method to construct a suitable gamma, in such a way that the individual impacts of model structure, model order and experimental conditions become visible, is presented. The technique is used to derive asymptotic variance expressions for a Hammerstein model and a nonlinear regression problem.

  • 20.
    Hjalmarsson, Håkan
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Finite model order accuracy in Hammerstein model estimation2012In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 48, no 10, p. 2640-2646Article in journal (Refereed)
    Abstract [en]

    Hammerstein models is one of the most commonly used model classes used for identifying nonlinear systems. A static input nonlinearity followed by a linear dynamical part is an adequate way to model many real-life systems. This paper investigates the asymptotic (in terms of sample size) variance of Hammerstein model estimates. The work extends earlier results by Ninness and Gibson (2002) in the following ways. Not only frequency function estimation but estimation of general quantities is considered. The expressions are not restricted to be valid asymptotically in the model order. In addition, the results cover model structures having noise models and allow for data generated under feedback. The increase in variance due to the estimation of the input nonlinearity is characterized. In particular, under open loop operation, white additive noise and the assumption of a separable process, it is shown that the variance increase is exactly a term that was observed in Ninness and Gibson (2002) to result in good agreement with simulations. This term vanishes in the formal asymptotic in model order analysis in Ninness and Gibson (2002).

  • 21.
    Hjalmarsson, Håkan
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Optimal input design for identification of non-linear systems: Learning from the linear case2007In: AMERICAN CONTROL CONFERENCE, 2007, p. 2325-2329Conference paper (Refereed)
    Abstract [en]

    For linear time-invariant systems, the input influences the accuracy of identified parameters only through its second order properties and its cross-correlation with the noise. A wide range of input design problems for such systems can be recast as semi-definite problems in the auto-correlation coefficients of the input or similar design variables. This allows for efficient numerical solutions of such problems. When the system is non-linear the situation is radically different. Nonlinearities can make the parameter accuracy depend on all moments of the input so that the accuracy may depend on the complete distribution of the input sequence. In this contribution we discuss some emerging ways to cope with this situation. In particular we illustrate how to formulate some input design problems as polynomial matrix inequalities for which relaxation methods exist which can generate a sequence of LMI problems with optimal values that under-bound the optimal solution and that converge to a global optimum of the original problem. Both deterministic and stochastic input models are considered. In the stochastic case we discuss how to delineate optimization of the statistical properties from the subsequent signal generation.

  • 22.
    Hjalmarsson, Håkan
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Rojas, Cristian R.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Söderström, Torsten
    Uppsala University.
    On the accuracy in errors-in-variables identification compared to prediction-error identification2011In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, ISSN 0005-1098, Vol. 47, no 12, p. 2704-2712Article in journal (Refereed)
    Abstract [en]

    Errors-in-variables estimation problems for single-inputsingle-output systems with Gaussian signals are considered in this contribution. It is shown that the Fisher information matrix is monotonically increasing as a function of the input noise variance when the noise spectrum at the input is known and the corresponding noise variance is estimated. Furthermore, it is shown that Whittle's formula for the Fisher information matrix can be represented as a Gramian and this is used to provide a geometric representation of the asymptotic covariance matrix for asymptotically efficient estimators. Finally, the asymptotic covariance of the parameter estimates for the system dynamics is compared for the two cases: (i) when the model includes white measurement noise on the input and the variance of the noise is estimated, and (ii) when the model includes only measurement noise on the output. In both cases, asymptotically efficient estimators are assumed. An explicit expression for the difference is derived when the underlying system is subject only to measurement noise on the output.

  • 23.
    Hjalmarsson, Håkan
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Wahlberg, Bo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    On Some Robustness Issues in Input Design2006In: IFAC Proceedings Volumes (IFAC-PapersOnline), 2006Conference paper (Refereed)
    Abstract [en]

    It is commonly believed that solutions to optimal input design problems for identification of dynamical systems often are sensitive to the underlying assumptions. For example, a wide class of problems can be solved with sinusoidal inputs with the same number of excitation frequencies (over the frequency range (-\p,\p]) as number of estimated parameters. With such an input it is not possible to check whether the true system is of higher order or not since then the input is not persistently exciting enough. In this contribution we argue that the optimal solution is often not unique and that there are alternatives to sinusoidal inputs which are more robust. For simplicity, we restrict attention to finite impulse-response models. For such a model of order n, it is only the n first auto-correlation coefficients of the input which determine the accuracy of the parameter estimate. Thus, the remaining coefficients can be used to make the solution more robust. For the problem of estimating some scalar system quantity J with a prescribed accuracy using minimum input energy, there is, under certain assumptions, an input spectrum that is optimal regardless of the model order. Furthermore, we show that using this input allows J to be estimated consistently even when the model order is lower than the true system order.

  • 24.
    Kokogias, Stefanos
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Svensson, Lars
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
    Pereira, Goncalo Collares
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Oliveira, Rui
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH Royal Inst Technol, Sch Elect Engn, Dept Automat Control, S-10044 Stockholm, Sweden..
    Zhang, Xinhai
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
    Song, Xinwu
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
    Mårtensson, Jonas
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Development of Platform-Independent System for Cooperative Automated Driving Evaluated in GCDC 20162018In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 19, no 4, p. 1277-1289Article in journal (Refereed)
    Abstract [en]

    Cooperative automated driving is a promising development in reducing energy consumption and emissions, increasing road safety, and improving traffic flow. The Grand Cooperative Driving Challenge (GCDC) 2016 was an implementation oriented project with the aim to accelerate research and development in the field. This paper describes the development of the two vehicle systems with which KTH participated in GCDC 2016. It presents a reference system architecture for collaborative automated driving as well as its instantiation on two conceptually different vehicles: a Scania truck and the research concept vehicle, built at KTH. We describe the common system architecture, as well as the implementation of a selection of shared and individual system functionalities, such as V2X communication, localization, state estimation, and longitudinal and lateral control. We also present a novel approach to trajectory tracking control for a four-wheel steering vehicle using model predictive control and a novel method for achieving fair data age distribution in vehicular communications.

  • 25. Liang, K. -Y
    et al.
    Martensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    When is it fuel eficient for a heavy duty vehicle to catch up with a platoon?2013In: IFAC Proceedings Volumes (IFAC-PapersOnline), 2013, no PART 1, p. 738-743Conference paper (Refereed)
    Abstract [en]

    Vehicle platooning has in recent years become an important research field for the vehicle industry. By establishing a platoon of heavy duty vehicles, the fuel consumption can be reduced for the follower vehicles due to the slipstream effect. However, as vehicles are scattered on the road driving by themselves, coordination amongst the vehicles is required. In this paper we study the problem of when it is beneficial for a heavy duty vehicle to drive faster in order to catch up and join a platoon. We derive a formula, based on at road and with no vehicle accelerations, to calculate if it is more fuel-eficient for a vehicle to drive faster and platoon or keep driving alone. Depending on the distance between the vehicles and the distance to the destination, the fuel savings vary. For a trip of 350 km, with a distance of 10km to the vehicle ahead, the fuel saving could be up to 7% if the follower vehicle decides to increase the speed from 80 km/h to 90 km/h in order to catch up and form a platoon, assuming an air drag reduction of 32% when platooning. Sensitivity analysis has shown that the speeds need to be relatively accurate in order to not give any false positive catch up decisions.

  • 26.
    Liang, Kuo-Yun
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. Scania CV AB, Sweden.
    Deng, Qichen
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Ma, Xiaoliang
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Transport Planning, Economics and Engineering.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    The Influence of Traffic on Heavy-Duty Vehicle Platoon Formation2015Conference paper (Refereed)
    Abstract [en]

    Heavy-duty vehicle (HDV) platooning is a mean to significantly reduce the fuel consumption for the trailing vehicle. By driving close to the vehicle in front, the air drag is reduced tremendously. Due to each HDV being assigned with different transport missions, platoons will need to be frequently formed, merged, and split. Driving on the road requires interaction with surrounding traffic and road users, which will influence how well a platoon can be formed. In this paper, we study how traffic may affect a merging maneuver of two HDVs trying to form a platoon. We simulate this for different traffic densities and for different HDV speeds. Even on moderate traffic density, a platoon merge could be delayed with 20% compared to the ideal case with no traffic. 

  • 27.
    Liang, Kuo-Yun
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. Scania CV AB, Sweden.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Experiments on Platoon Formation of Heavy Trucks in Traffic2016In: 2016 IEEE 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), IEEE, 2016, p. 1813-1819Conference paper (Refereed)
    Abstract [en]

    Truck platooning is a means to significantly reduce the fuel consumption for the follower vehicle as the air drag is reduced when the inter-vehicle gap between the trucks is reduced. As each truck is assigned with different start and end locations, platoons will be frequently formed and split, while driving to their respective destinations. Additionally, the trucks are not the only ones driving on the road as there are other road users, which may influence how well a platoon can be formed. In this paper, an experimental study is conducted to investigate how traffic may affect a merging maneuver of two trucks trying to form a platoon on a public highway during rush hours. We obtained traffic data from Stockholm's motorway control system to determine the traffic condition for each testrun. Furthermore, we tried different truck speeds to study if it had any impacts on merge delay. Even in light traffic condition, a platoon merge could be delayed with over 10 % compared to the ideal case with the absence of traffic. This is partially caused by persistent drivers in which we encountered them in a fourth of the runs.

  • 28.
    Liang, Kuo-Yun
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. Scania CV AB, Sweden.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fuel-Saving Potentials of Platooning Evaluated through Sparse Heavy-Duty Vehicle Position Data2014Conference paper (Refereed)
    Abstract [en]

    Vehicle platooning is important for heavy-duty vehicle manufacturers, due to the reduced aerodynamic drag for the follower vehicles, which gives an overall lower fuel consumption. Heavy-duty vehicle drivers are aware this fact and sometimes drive close to other heavy-duty vehicles. However, it is not currently well known how many vehicles are actually driving in such spontaneous platoons today. This paper studies the platooning rate of 1,800 heavy-duty vehicles by analyzing sparse vehicle position data from a region in Europe during one day. Map-matching and path-inference algorithms are used to determine which paths the vehicles took. The spontaneous platooning rate is found to be 1.2 %, which corresponds to a total fuel saving of 0.07% compared to if none of the vehicles were platooning. Furthermore, we introduce several virtual coordination schemes. We show that coordinations can increase the platooning rate and fuel saving with a factor of ten with minor adjustments from the current travel schedule. The platooning rate and fuel savings can be significantly greater if higher flexibility is allowed.

  • 29.
    Liang, Kuo-Yun
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Heavy-Duty Vehicle Platoon Formation for Fuel Efficiency2016In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 17, no 4, p. 1051-1061Article in journal (Refereed)
    Abstract [en]

    Heavy-duty vehicles driving close behind each other, also known as platooning, experience a reduced aerodynamic drag, which reduces the overall fuel consumption up to 20% for the trailing vehicle. However, due to each vehicle being assigned with different transport missions (with different origins, destinations, and delivery times), platoons should be formed, split, and merged along the highways, and vehicles have to drive solo sometimes. In this paper, we study how two or more scattered vehicles can cooperate to form platoons in a fuel-efficient manner. We show that when forming platoons on the fly on the same route and not considering rerouting, the road topography has a negligible effect on the coordination decision. With this, we then formulate an optimization problem when coordinating two vehicles to form a platoon. We propose a coordination algorithm to form platoons of several vehicles that coordinates neighboring vehicles pairwise. Through a simulation study with detailed vehicle models and real road topography, it is shown that our approach yields significant fuel savings.

  • 30.
    Liang, Kuo-Yun
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control.
    When is it Fuel Efficient for a Heavy Duty Vehicle to Catch Up With a Platoon?2013Conference paper (Refereed)
    Abstract [en]

    Vehicle platooning has in recent years become an important research eld for thevehicle industry. By establishing a platoon of heavy duty vehicles, the fuel consumption can bereduced for the follower vehicles due to the slipstream eect. However, as vehicles are scatteredon the road driving by themselves, coordination amongst the vehicles is required. In this paperwe study the problem of when it is benecial for a heavy duty vehicle to drive faster in orderto catch up and join a platoon. We derive a formula, based on at road and with no vehicleaccelerations, to calculate if it is more fuel-ecient for a vehicle to drive faster and platoonor keep driving alone. Depending on the distance between the vehicles and the distance to thedestination, the fuel savings vary. For a trip of 350 km, with a distance of 10km to the vehicleahead, the fuel saving could be up to 7% if the follower vehicle decides to increase the speed from80 km/h to 90 km/h in order to catch up and form a platoon, assuming an air drag reductionof 32% when platooning. Sensitivity analysis has shown that the speeds need to be relativelyaccurate in order to not give any false positive catch up decisions.

  • 31.
    Liang, Kuo-Yun
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    van de Hoef, Sebastian
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Terelius, Hakan
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Turri, Valerio
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Besselink, Bart
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Martensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Networked control challenges in collaborative road freight transport2016In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 30, p. 2-14Article in journal (Refereed)
    Abstract [en]

    Freight transport is of major importance for the European economy and is growing thanks to increasing global trade. About three quarters of inland freight transport in the European Union is on roads. It has the potential to go through a dramatic change over the next decades thanks to the recent development of technologies such as wireless communication, cloud computing, sensor devices, and vehicle electronics. They enable a new integrated goods transport system based on optimized logistics, real-time traffic information, vehicular communications, collaborative driving, and autonomous vehicles. In this paper, we discuss challenges in creating a more efficient and sustainable goods road transportation system and how some of them can be tackled with a networked control approach. In particular, we discuss a method to improve the efficiency of the transportation system by minimizing the number of empty transports needed to fulfill the assignments on a given road network. Assignments with overlapping route segments might lead to further improvements, as the formation of vehicle platoons yields reduced fuel consumption. For realistic scenarios, it is shown that such collaboration opportunities arise already with relatively few vehicles. The fuel-efficient formation and control of platoons is also discussed. Some of the presented methods have been tested on real vehicles in traffic. The paper shows experimental results on automatic formation of vehicle platoons on a Swedish highway. The influence of traffic density on the merge maneuver is illustrated. The results indicate that platoon coordination could be improved by support from appropriate traffic monitoring technologies.

  • 32.
    Lima, Pedro F.
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Wahlberg, Bo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Stability Conditions for Linear Time-Varying Model Predictive Control in Autonomous Driving2017In: 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017, IEEE, 2017, p. 2775-2782Conference paper (Refereed)
    Abstract [en]

    This paper presents stability conditions when designing a linear time-varying model predictive controller for lateral control of an autonomous vehicle. Stability is proved via Lyapunov techniques by adding a terminal state constraint and a terminal cost. We detail how to compute the terminal state and the terminal cost for the linear time-varying case, and interpret the obtained results in the light of an autonomous driving application. To determine the stability conditions, the concept of multi-model description is used, where the linear time-varying model is separated into a finite number of time- invariant models that depend on a single parameter. The terminal set is the maximum positive invariant set of the multi- model description and the terminal cost is the result of a min-max optimization that determines the worst time-invariant model if used as a prediction model. In fact, in the autonomous driving case, we show that the min-max approach is a convex optimization problem. The stability conditions are computed offline, maintain the convexity of the optimization, and do not affect the execution time of the controller. In simulation, we demonstrate the stabilizing effectiveness of the proposed conditions through an illustrative example of path following with a heavy-duty vehicle. 

  • 33.
    Lima, Pedro F.
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Nilsson, Mattias
    Trincavelli, Marco
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Wahlberg, Bo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Experimental evaluation of economic model predictive control for an autonomous truck2016Conference paper (Refereed)
    Abstract [en]

    In this paper, we propose a controller for smooth autonomous path following. The controller is formulated as an economic model predictive controller. The economic cost introduced in the objective function leads to a smooth driving, since we minimize the first and second derivatives of the curvature function (i.e., we encourage linear curvature profiles). Since the curvature in clothoids varies linearly with the path arc-length, we use the smoothness and comfort characteristics of clothoid-driving to obtain a compact and intuitive controller formulation. We enforce convergence of the controller to the reference path with soft constraints that avoid deviations from the reference path. Finally, we present real life experiments where the controller is deployed on a Scania construction truck that show that the proposed controller outperforms a pure-pursuit controller. Moreover, we detail how the few tuning parameters can affect the obtained solution in practice.

  • 34.
    Lima, Pedro F.
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Nilsson, Mattias
    Trincavelli, Marco
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Wahlberg, Bo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Spatial Model Predictive Control for Smooth and Accurate Steering of an Autonomous Truck2017In: IEEE Transactions on Intelligent Vehicles, ISSN 2379-8858, Vol. 2, no 4, p. 238-250Article in journal (Refereed)
    Abstract [en]

    In this paper, we present an algorithm for lateral control of a vehicle – a smooth and accurate model predictive controller. The fundamental difference compared to a standard MPC is that the driving smoothness is directly addressed in the cost function. The controller objective is based on the minimization of the first- and second-order spatial derivatives of the curvature. By doing so, jerky commands to the steering wheel, which could lead to permanent damage on the steering components and vehicle structure, are avoided. A good path tracking accuracy is ensured by adding constraints to avoid deviations from the reference path. Finally, the controller is experimentally tested and evaluated on a Scania construction truck. The evaluation is performed at Scania’s facilities near So ̈derta ̈lje, Sweden via two different paths: a precision track that resembles a mining scenario and a high-speed test track that resembles a highway situation. Even using a linearized kinematic vehicle to predict the vehicle motion, the performance of the proposed controller is encouraging, since the deviation from the path never exceeds 30 cm. It clearly outperforms an industrial pure-pursuit controller in terms of path accuracy and a standard MPC in terms of driving smoothness. 

  • 35.
    Lima, Pedro F.
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Oliveira, Rui
    Scania CV AB, Res & Dev, S-15187 Södertalje, Sweden..
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.
    Wahlberg, Bo
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.
    Minimizing Long Vehicles Overhang Exceeding the Drivable Surface via Convex Path Optimization2017In: 2017 IEEE 20TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    This paper presents a novel path planning algorithm for on-road autonomous driving. The algorithm targets long and wide vehicles, in which the overhangs (i.e., the vehicle chassis extending beyond the front and rear wheelbase) can endanger other vehicles, pedestrians, or even the vehicle itself. The vehicle motion is described in a road-aligned coordinate frame. A novel method for computing the vehicle limits is proposed guaranteeing feasibility of the planned path when converted back into the original coordinate frame. The algorithm is posed as a convex optimization that takes into account the exact dimensions of the vehicle and the road, while minimizing the amount of overhang outside of the drivable surface. The results of the proposed algorithm are compared in a simulation of a real road scenario against a centerline tracking scheme. The results show a significant decrease on the amount of overhang area outside of the drivable surface, leading to an increased safety in driving maneuvers. The real-time applicability of the method is shown, by using it in a recedinghorizon framework.

  • 36.
    Lima, Pedro F.
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Trincavelli, Marco
    Scania CV AB.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Wahlberg, Bo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Clothoid-Based Model Predictive Control for Autonomous Driving2015Conference paper (Refereed)
    Abstract [en]

    This paper presents a novel linear time-varying model predictive controller (LTV-MPC) using a sparse clothoid-based path description: a LTV-MPCC. Clothoids are used world-wide in road design since they allow smooth driving associated with low jerk values. The formulation of the MPC controller is based on the fact that the path of a vehicle traveling at low speeds defines a segment of clothoids if the steering angle is chosen to vary piecewise linearly. Therefore, we can compute the vehicle motion as clothoid parameters and translate them to vehicle inputs. We present simulation results that demonstrate the ability of the controller to produce a very comfortable and smooth driving while maintaining a tracking accuracy comparable to that of a regular LTV-MPC. While the regular MPC controllers use path descriptions where waypoints are close to each other, our LTV-MPCC has the ability of using paths described by very sparse waypoints. In this case, each pair of waypoints describes a clothoid segment and the cost function minimization is performed in a more efficient way allowing larger prediction distances to be used. This paper also presents a novel algorithm that addresses the problem of path sparsification using a reduced number of clothoid segments. The path sparsification enables a path description using few waypoints with almost no loss of detail. The detail of the reconstruction is an adjustable parameter of the algorithm. The higher the required detail, the more clothoid segments are used.

  • 37.
    Lima, Pedro F.
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Trincavelli, Marco
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Wahlberg, Bo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Clothoid-Based Speed Profiler and Control for Autonomous Driving2015In: 2015 IEEE 18th International Conference on Intelligent Transportation Systems, IEEE conference proceedings, 2015Conference paper (Refereed)
    Abstract [en]

    This paper presents a method for optimal speed profile generation in specified clothoid-based paths with known semantic – maximum speed and longitudinal and lateral acceleration – and geometric information. A clothoid can be described using only its kink-points information, i.e. the points defining the start and end of a clothoid. Using the clothoid-based path representation, we formulate the speed profile generation as a convex optimization problem where the objective is to produce a smooth speed that is close to the maximum allowed speed. The vehicle and the road profile define the constraints of the problem. Furthermore, we develop a longitudinal controller by using the speed profiler in a receding-horizon fashion. Thus, we only consider a finite horizon when computing the optimal inputs every sampling time and, in addition, the longitudinal controller also takes into account the newest prediction available from measurements and from the lateral controller. We present simulations that demonstrate the ability of the method to generate safe and feasible speed profiles and the tracking of those by the longitudinal controller. We also study the influence of the clothoid-based path representation in the optimality of the speed profile obtained. We show that we can get a very good suboptimal speed profile approximation with few more points than the kink-points. In addition, we analyze the influence of an acceleration penalization factor in the smoothness of the speed profiler. The higher the acceleration penalization the smoother and the further from the maximum allowed speed is the speed profile.

  • 38.
    Ma, Xiaoliang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics. KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Traffic Research, CTR.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Optimal control of vehicle trajectory based on vehicle to infrastructure Information2012Report (Other academic)
  • 39.
    Ma, Xiaoliang
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Transport Science, Traffic and Logistics.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Optimal controls of vehicle trajectories in fleet management using V2I information2012In: Proceedings - 2012 International Conference on Connected Vehicles and Expo, ICCVE 2012, IEEE , 2012, p. 256-260Conference paper (Refereed)
    Abstract [en]

    Given the raised focus on transport energy and traffic-induced environmental issues, the ability of reducing vehicular environmental impacts is of great importance for intelligent traffic management. The recent development in vehicle-to-infrastructure (V2I) communication provides an effective means for continuous management of vehicle driving. This study presents an essential step of the work towards a dynamic fleet management system that takes advantages of real-time traffic information and communication. Based on the optimal control theory, a methodological approach is developed to control the environmental impacts of live vehicle fleets. In particular, vehicle trajectories that minimize local environmental objectives are derived by applying a discrete dynamic programming method. Numerical examples show that the method is promising for local V2I based traffic management applications and can be further extended for more complex optimal control problems in dynamic fleet management.

  • 40.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Geometric analysis of stochastic model errors in system identification2007Doctoral thesis, comprehensive summary (Other scientific)
    Abstract [en]

    Models of dynamical systems are important in many disciplines of science, ranging from physics and traditional mechanical and electrical engineering to life sciences, computer science and economics. Engineers, for example, use models for development, analysis and control of complex technical systems. Dynamical models can be derived from physical insights, for example some known laws of nature, (which are models themselves), or, as considered here, by fitting unknown model parameters to measurements from an experiment. The latter approach is what we call system identification. A model is always (at best) an approximation of the true system, and for a model to be useful, we need some characterization of how large the model error is. In this thesis we consider model errors originating from stochastic (random) disturbances that the system was subject to during the experiment.

    Stochastic model errors, known as variance-errors, are usually analyzed under the assumption of an infinite number of data. In this context the variance-error can be expressed as a (complicated) function of the spectra (and cross-spectra) of the disturbances and the excitation signals, a description of the true system, and the model structure (i.e., the parametrization of the model). The primary contribution of this thesis is an alternative geometric interpretation of this expression. This geometric approach consists in viewing the asymptotic variance as an orthogonal projection on a vector space that to a large extent is defined from the model structure. This approach is useful in several ways. Primarily, it facilitates structural analysis of how, for example, model structure and model order, and possible feedback mechanisms, affect the variance-error. Moreover, simple upper bounds on the variance-error can be obtained, which are independent of the employed model structure.

    The accuracy of estimated poles and zeros of linear time-invariant systems can also be analyzed using results closely related to the approach described above. One fundamental conclusion is that the accuracy of estimates of unstable poles and zeros is little affected by the model order, while the accuracy deteriorates fast with the model order for stable poles and zeros. The geometric approach has also shown potential in input design, which treats how the excitation signal (input signal) should be chosen to yield informative experiments. For example, we show cases when the input signal can be chosen so that the variance-error does not depend on the model order or the model structure.

    Perhaps the most important contribution of this thesis, and of the geometric approach, is the analysis method as such. Hopefully the methodology presented in this work will be useful in future research on the accuracy of identified models; in particular non-linear models and models with multiple inputs and outputs, for which there are relatively few results at present.

  • 41.
    Mårtensson, Jonas
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Alam, Assad
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Behere, Sagar
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Khan, Altamash
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Kjellberg, Joakim
    Liang, Kuo-Yun
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Pettersson, Henrik
    Sundman, Dennis
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    The development of a cooperative heavy-duty vehicle for the GCDC 2011: Team Scoop2012In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 13, no 3, p. 1033-1049Article in journal (Refereed)
    Abstract [en]

    The first edition of the Grand Cooperative Driving Challenge (GCDC) was held in the Netherlands in May 2011. Nine international teams competed in urban and highway platooning scenarios with prototype vehicles using cooperative adaptive cruise control. Team Scoop, a collaboration between KTH Royal Institute of Technology, Stockholm, Sweden, and Scania CV AB, Sodertalje, Sweden, participated at the GCDC with a Scania R-series tractor unit. This paper describes the development and design of Team Scoop's prototype system for the GCDC. In particular, we present considerations with regard to the system architecture, state estimation and sensor fusion, and the design and implementation of control algorithms, as well as implementation issues with regard to the wireless communication. The purpose of the paper is to give a broad overview of the different components that are needed to develop a cooperative driving system: from architectural design, workflow, and functional requirement descriptions to the specific implementation of algorithms for state estimation and control. The approach is more pragmatic than scientific; it collects a number of existing technologies and gives an implementation-oriented view of a cooperative vehicle. The main conclusion is that it is possible, with a modest effort, to design and implement a system that can function well in cooperation with other vehicles in realistic traffic scenarios.

  • 42.
    Mårtensson, Jonas
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Everitt, Niklas
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Covariance analysis in SISO linear systems identification2017In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 77, p. 82-92Article in journal (Refereed)
    Abstract [en]

    In this paper, we analyze the asymptotic covariance of models of causal single-input single-output linear time invariant systems. Expressions for the asymptotic (co)variance of system properties estimated using the prediction error method are derived. These expressions delineate the impacts of model structure, model order, true system dynamics, and experimental conditions. A connection to results on frequency function estimation is established. Also, simple model structure independent upper bounds are derived. Explicit variance expressions and bounds are provided for common system properties such as impulse response coefficients and non-minimum phase zeros. As an illustration of the insights the expressions provide, they are used to derive conditions on the input spectrum which make the asymptotic variance of non-minimum phase zero estimates independent of the model order and model structure.

  • 43.
    Mårtensson, Jonas
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Everitt, Niklas
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Variance Analysis in SISO Linear Systems Identification2015In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836Article in journal (Refereed)
    Abstract [en]

    Causal single input single output linear time invariant systems are considered. Expressions for the asymptotic (co)variance of system properties estimated using the prediction error method are derived. These expressions delineate the impacts of model structure, model order, true system dynamics, and experimental conditions. A connection to results on frequency function estimation is established. Also, simple model structure independent upper bounds are derived. Explicit variance expressions and bounds are provided for common system properties such as impulse response coefficients and non-minimum phase zeros. As an illustration of the insights the expressions provide, they are used to derive conditions on the input spectrum which makethe asymptotic variance of non-minimum phase zero estimates independent of the model order and model structure.

  • 44.
    Mårtensson, Jonas
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Flärdh, Oscar
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Modeling the Effect of Variable Cam Phasing on Volumetric Efficiency, Scavenging and Torque Generation2010In: SAE 2010 World Congress & Exhibition, 2010Conference paper (Refereed)
    Abstract [en]

    In a mean value engine model, the mass flow of air through the cylinders is, up to a constant factor, described as the product of the air density in the intake manifold, the engine speed, and the volumetric efficiency. The volumetric efficiency is traditionally modeled as a function of the engine speed and the pressure in the intake and exhaust manifolds, but for modern engines the model must also account for the effect of variable valve timings. The engine that is modeled here is equipped with variable cam phasing on both the intake and the exhaust valves. In order to reduce the complexity, we will only model the effect of the valve overlap, which is the number of crank angle degrees that both valves are open simultaneously. When the valve overlap is significant, there may be fresh air that flows directly through the exhaust valve, known as scavenging. The scavenging will cause the air/fuel ratio of the gas mixture in the cylinder to be different than the global air/fuel ratio, and it has effects both on the torque generation from the combustion and on the temperature and pressure of the exhaust gases that drive the turbine as well as on the emission levels from the engine. The degree of scavenging cannot be measured directly on the engine and for that part of the modeling we use GT POWER simulations. The simulations show that the scavenging can be modeled as a function of the volumetric efficiency. A torque model is derived as a tool to validate the scavenging model. The new models are shown to improve the predictions of the engine torque significantly.

  • 45.
    Mårtensson, Jonas
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Flärdh, Oscar
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Modeling the effect of variable cam phasing on volumetric efficiency, scavenging and torque generation in SI enginesIn: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939Article in journal (Other academic)
    Abstract [en]

    In a mean value engine model, the mass flow of air through thecylinders is determined by the air density, the engine speed, and thevolumetric efficiency. For modern engines the volumetric efficiency model mustalso account for the effect of variable valve timings. In this work the effect of the valve overlap is considered. Thevalve overlap is the number of crank angle degrees that both valvesare open simultaneously. When the valve overlap is significant,there may be fresh air that flows directly through the exhaustvalve, known as scavenging, which affects the torque. Steady-state torque measurements are used to estimate the amount of scavenging. The volumetric efficiency and scavenging models derived in the paper are shown toimprove the predictions of the engine torque significantly, alsounder transient conditions.

  • 46.
    Mårtensson, Jonas
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A geometric approach to variance analysis in system identification: Linear Time-Invariant Systems2007In: PROCEEDINGS OF THE 46TH IEEE CONFERENCE ON DECISION AND CONTROL, 2007, no ThC11.5, p. 4269-4274Conference paper (Refereed)
    Abstract [en]

    This paper addresses the problem of quantifying the model error ("variance-error") in estimates of linear time invariant systems. Building on the results in H. Hjalmarsson and J. Martensson (2007), we present an explicit method to construct an expression for the asymptotic variance of system properties such as impulse response coefficients, system gain, or the performance of some (control) application where the identified model is used. The expression is such that the individual impacts of model structure, model order and experimental conditions become visible. The technique is used to derive asymptotic variance expressions for a number of system properties.

  • 47.
    Mårtensson, Jonas
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Closed loop identification of unstable poles and non-minimum phase zeros2005In: IFAC Proceedings Volumes (IFAC-PapersOnline), Prague, 2005, Vol. 16, p. 518-523Conference paper (Refereed)
    Abstract [en]

    This paper addresses estimation of poles and zeros in closed loop systems. For many quantities of interest, e.g. frequency function estimates, overparameterization results in a large increase of the variance but this is not the case for estimates of nonminimum phase zeros and unstable poles. Variance expressions that are asymptotic in model order and sample size are derived and for some systems it is found that open loop and closed loop experiments give the same accuracy.

  • 48.
    Mårtensson, Jonas
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Exact quantification of the variance of estimated zeros2005In: 44th IEEE Conference on Decision and Control & European Control Conference, 2005, p. 4275-4280Conference paper (Refereed)
    Abstract [en]

    This paper is concerned with quantification of noise induced errors in estimates of zeros of dynamic systems. Preceding work on this problem has provided variance expressions that are asymptotic in data length and model order for non-minimum phase zeros. This paper presents expressions that are asymptotic only in data length and they are therefore 'exact' for arbitrarily small true model orders. These expressions are also valid for both minimum phase and non-minimum phase zeros. A key insight is that the variance error quantification problem is equivalent to deriving a reproducing kernel for a space that depends on the employed model structure.

  • 49.
    Mårtensson, Jonas
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    How to Make Bias and Variance Errors Insensitive to System and Model Complexity in Identification2011In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 56, no 1, p. 100-112Article in journal (Refereed)
    Abstract [en]

    Solutions to optimal input design problems for system identification are sometimes believed to be sensitive to the underlying assumptions. For example, a wide class of problems can be solved with sinusoidal inputs with the same number of excitation frequencies (over the frequency range (-pi, pi]) as the number of model parameters. The order of the true system is in many cases unknown and, hence, so is the required number of frequencies in the input. In this contribution we characterize when and how the input spectrum can be chosen so that the (asymptotic) variance error of a scalar function of the model parameters becomes independent of the order of the true system. A connection between these robust designs and the solutions of certain optimal input design problems is also made. Furthermore, we show that there are circumstances when using this type of input allows some model properties to be estimated consistently even when the model order is lower than the order of the true system. The results are derived under the assumptions of causal linear time invariant systems operating in open loop and excited by an input signal having a rational spectral factor with all poles and zeros strictly inside the unit circle.

  • 50.
    Mårtensson, Jonas
    et al.
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Hjalmarsson, Håkan
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Identification of performance limitations using general SISO structures2003In: Proceedings 13th IFAC Symposium on System Identification, 2003, p. 519-524Conference paper (Refereed)
12 1 - 50 of 68
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