Robust model predictive control of discrete nonlinear systems with time delays and disturbances via T–S fuzzy approach

Long Teng, Youyi Wang, Wenjian Cai, Hua Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

37 Citations (Scopus)

Abstract

In this paper, robust fuzzy model predictive control of a class of nonlinear discrete systems subjected to time delays and persistent disturbances is investigated. Based on the modeling method of delay difference inclusions, nonlinear discrete time-delay systems can be represented by T–S fuzzy systems comprised of piecewise linear delay difference equations. Moreover, Lyapunov–Razumikhin function (LRF), instead of Lyapunov–Krasovskii functional (LKF), is employed for time-delay systems due to its ability to reflect system original state space and its advantages in controller synthesis and computation. The robust positive invariance and input-to-state stability with respect to disturbance under such circumstances are investigated. A robust constraint set is adopted that the system state is converged to this set round the desired point. In addition, the controller synthesis conditions are derived by solving a set of matrix inequalities. Simulation results show that the proposed approach can be successfully applied to the well-known continuous stirred tank reactor (CSTR) systems subjected to time delay.

Original languageEnglish
Pages (from-to)70-79
Number of pages10
JournalJournal of Process Control
Volume53
DOIs
Publication statusPublished - May 2017
Externally publishedYes

Keywords

  • Input-to-state stability
  • Lyapunov–Razumikhin
  • Model predictive control
  • Time delay
  • T–S fuzzy systems

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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