Stability analysis of a multi-model predictive control algorithm with application to control of chemical reactors

Leyla Özkan, Mayuresh V. Kothare

Research output: Contribution to journalArticlepeer-review

Abstract

We study a stabilizing multi-model predictive control strategy for controlling nonlinear process at different operating conditions. The control algorithm is a receding horizon scheme with a quasi-infinite horizon objective function that has finite and infinite horizon cost components. The finite horizon cost consists of free input variables that direct the system towards a terminal region which contains the desired operating point. The infinite horizon cost has an upper bound and steers the system to the desired operating point. The system is represented by a sequence of piecewise linear models. Based on the condition of the system states, the sequence of piecewise linear models is updated and the controller's objective function switches form quasi-infinite to infinite horizon objective function. This results in a hybrid control structure. A recent approach in the analysis of hybrid systems that uses multiple Lyapunov functions is employed in the stability analysis of the closed-loop system. The stabilizing hybrid control strategy is illustrated on two examples and their closed-loop stability properties are studied.

Original languageEnglish (US)
Pages (from-to)81-90
Number of pages10
JournalJournal of Process Control
Volume16
Issue number2
DOIs
StatePublished - Feb 2006
Externally publishedYes

Keywords

  • Hybrid systems
  • Linear matrix inequalities
  • Model predictive control
  • Multiple models
  • Stability

ASJC Scopus subject areas

  • Process Chemistry and Technology
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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