Stability analysis of classic finite horizon model predictive control

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23 Citations (Scopus)

Abstract

This paper revisits the stability issue of earlier model predictive control (MPC) algorithms where the performance index has a finite receding horizon and there is no terminal penalty in the performance index or other constraints added in online optimisation for the purpose of stability. Stability conditions are presented for MPC of constrained linear and nonlinear systems, and there is no restriction on the length of the horizon. These conditions can be used to test whether or not desired stability properties can be achieved under chosen state and control weightings.

Original languageEnglish
Pages (from-to)187-197
Number of pages11
JournalInternational Journal of Control, Automation and Systems
Volume8
Issue number2
DOIs
Publication statusPublished - Apr 2010

Keywords

  • Constrained control
  • Finite horizon
  • Lyapunov theory
  • Nonlinear systems
  • Predictive control
  • Stability

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications

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