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Optimal Input Design by Model Predictive Control for System Identification
KTH, School of Electrical Engineering (EES), Automatic Control.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Mathematical models are an essential part of analysis of autonomous systemsas they ease the formulation of control laws and allow experiments tobe performed in a simulation environment. For complex systems, parts of themodel may be missing which increases uncertainties and limits practical applications.Using input-output measurements makes it possible to estimate themodel, but requires the measurements to be informative. The idea in so-calledinput design is to find an input sequence for the system such that the measurementsreveal the properties and dynamics of the true system as much aspossible. This is commonly formulated as an optimization problem.This thesis focuses on formulating an optimization algorithm for inputdesign, which is implemented as an open-loop receding horizon optimizationproblem. The problem consists of classical A-, D-, E-optimality criteria andfinite combinatorial constraints on the input signal. The resulting optimizationproblem is non-convex. Two approaches are explored to solve the problem;a combinatorial and a convex relaxation. The method is finally evaluated ina simulation environment on a second-order system and first-order linearizedwater tank system.

Abstract [sv]

Matematiska modeller är essentiella när det kommer till autonoma systemeftersom det förenklar formuleringar av styrlagar och tillåter tester i simuleringsmiljöer.För komplexa system kan delar av modellen saknas vilket ökarosäkerheten hos modellen och begränsar praktiska tillämpningar. Genom attanvända in-ut data är det möjligt att estimera modellen men det kräver attmätningarna är av relativ kvalitet. Idén är således att finna en sekvens av indataså att dynamiken hos systemet avslöjas vilket kan formuleras som ettoptimeringsproblem.Det här arbetet fokuserar på att formulera ett optimeringsproblem somska implementeras i modell prediktiv reglering. Problemet består utav klassiskA,D, E-optimalitet med begränsade diskreta bivillkor på insignalen. Metodenevalueras i simulering på ett godtyckligt andra ordningens system och på ettlineariserat första ordningens vattentankssystem.

Place, publisher, year, edition, pages
2017. , p. 51
Series
TRITA-EE, ISSN 1653-5146 ; 2017:145
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-215712OAI: oai:DiVA.org:kth-215712DiVA, id: diva2:1149084
Educational program
Master of Science - Systems, Control and Robotics
Available from: 2017-10-13 Created: 2017-10-13 Last updated: 2017-10-13Bibliographically approved

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CiteExportLink to record
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