Robust fuzzy model predictive control of discrete-time takagi-sugeno systems with nonlinear local models

Long Teng, Youyi Wang, Wenjian Cai, Hua Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

35 Citations (Scopus)

Abstract

Robust fuzzy model predictive control of discrete nonlinear systems is investigated in this paper. A recently developed Takagi-Sugeno (T-S) fuzzy approach which uses nonlinear local models is adopted to approximate the nonlinear systems. A critical issue that restricts the practical application of classical model predictive control is the online computational cost. For model predictive control of T-S fuzzy systems, the online computational burden is even worse. Especially for complex systems with severe nonlinearities, parametric uncertainties, and disturbances, existing model predictive control of T-S fuzzy systems usually leads to a very conservative solution or even no solution in some occasions. However, more relaxed results can be achieved by the proposed fuzzy model predictive control approach which adopts T-S systems with nonlinear local models. Another advantage is that online computational cost of the optimization problem through solving matrix inequalities can be significantly reduced at the same time. Simulations on a numerical example and a two-tank system are presented to verify the effectiveness and advantages of the proposed method. Comparisons among several T-S fuzzy approaches are illustrated and show that the best settling time is achieved via the proposed method.

Original languageEnglish
Article number8315042
Pages (from-to)2915-2925
Number of pages11
JournalIEEE Transactions on Fuzzy Systems
Volume26
Issue number5
DOIs
Publication statusPublished - Oct 2018
Externally publishedYes

Keywords

  • Input-to-state stability
  • model predictive control (MPC)
  • robust control
  • T-S fuzzy systems

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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