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Explicit MPC for LPV Systems: Stability and Optimality
ABB, Switzerland .
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
ETH Zürich, Switzerland .
2012 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 57, no 9, 2322-2332 p.Article in journal (Refereed) Published
Abstract [en]

This paper considers high-speed control of constrained linear parameter-varying systems using model predictive control. Existing model predictive control schemes for control of constrained linear parameter-varying systems typically require the solution of a semi-definite program at each sampling instance. Recently, variants of explicit model predictive control were proposed for linear parameter-varying systems with polytopic representation, decreasing the online computational effort by orders of magnitude. Depending on the mathematical structure of the underlying system, the constrained finite-time optimal control problem can be solved optimally, or close-to-optimal solutions can be computed. Constraint satisfaction, recursive feasibility and asymptotic stability can be guaranteed a priori by an appropriate selection of the terminal state constraints and terminal cost. The paper at hand gathers previous developments and provides new material such as a proof for the optimality of the solution, or, in the case of close-to-optimal solutions, a procedure to determine a bound on the suboptimality of the solution.

Place, publisher, year, edition, pages
2012. Vol. 57, no 9, 2322-2332 p.
Keyword [en]
Constrained control, Dynamic programming, Explicit model predictive control (MPC), Linear parameter-varying (LPV) systems, Optimal control
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-84340DOI: 10.1109/TAC.2012.2187400ISI: 000308104700012OAI: diva2:558818
Available from: 2012-10-05 Created: 2012-10-05 Last updated: 2013-07-23

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