Stabilizing model predictive control for LPV systems subject to constraints with parameter-dependent control law

  • Authors:

  • Shuyou Yu;Christoph Böhm;Hong Chen;Frank Allgöwer

  • Affiliations:

  • Institute of Systems Theory and Automatic Control, University of Stuttgart, Germany and Jilin University, China;Institute of Systems Theory and Automatic Control, University of Stuttgart, Germany;Jilin University, China;Institute of Systems Theory and Automatic Control, University of Stuttgart, Germany

  • Venue:
  • ACC'09 Proceedings of the 2009 conference on American Control Conference
  • Year:
  • 2009

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Abstract

This paper presents an infinite horizon model predictive control (MPC) scheme for constrained linear parameter-varying systems. We assume that the time-varying parameter can be measured online and exploited for feedback. The proposed method is based on a parameter-dependent control law which is obtained via the repeated solution of a convex optimization problem involving linear matrix inequalities (LMIs). Closed-loop stability is guaranteed by the feasibility of the LMIs at initial time. Compared to existing algorithms with static linear control law and more restrictive LMI conditions, the proposed scheme reduces conservatism and improves performance, which is confirmed by a simulation example.