An optimal approach to output-feedback robust model predictive control of LPV systems with disturbances

Weilin Yang, Jianwei Gao, Gang Feng, Tie Jun Zhang

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

An observer-based output feedback predictive control approach is proposed for linear parameter varying systems with norm-bounded external disturbances. Sufficient and necessary robust positively invariant set conditions of the state estimation error are developed to determine the minimal ellipsoidal robust positively invariant set and observer gain through offline computation. The quadratic upper bound of state estimation error is updated and included in an H -type cost function of predictive control to optimize transient output feedback control performance. Recursive feasibility of the dynamic convex optimization problem is guaranteed in the proposed predictive control strategy. With the input-to-state stable observer, the closed-loop control system states are steered into a bounded set. Simulation results are given to demonstrate the effectiveness of the proposed control strategy.

Original languageBritish English
Pages (from-to)3253-3273
Number of pages21
JournalInternational Journal of Robust and Nonlinear Control
Volume26
Issue number15
DOIs
StatePublished - 1 Oct 2016

Keywords

  • LPV systems
  • model predictive control
  • output feedback
  • robust control

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