Optimisation of attraction domains of nonlinear MPC via LMI methods

Wen Hu Chen, Donald J. Ballance, John O’Reilly

Research output: Journal article publicationJournal articleAcademic researchpeer-review

41 Citations (Scopus)

Abstract

This paper addresses the attraction domain of Model-Based Predictive Control (MPC) for nonlinear systems with control input and state constraints. Based on a stability condition of nonlinear MPC, a method to determine the terminal weighting term in the performance index and the terminal stabilising control law to maximise the domain of attraction of the nonlinear MPC is proposed. The problem of maximisation of the attraction region is recast as a well-defined optimisation problem. By an LMI based optimisation approach, the terminal weighting item and fictitious terminal stabilising control law are optimised to enlarge the attraction domain and hence the feasibility domain of the nonlinear MPC method. The proposed method is illustrated by a numerical example and favourably compared with existing results.

Original languageEnglish
Pages (from-to)3067-3072
Number of pages6
JournalProceedings of the American Control Conference
Volume4
DOIs
Publication statusPublished - 2001

Keywords

  • LMI's
  • Model-based predictive control
  • Nonlinear systems
  • Optimisation
  • Stability

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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