Multivariable adaptive output tracking control of T-S fuzzy systems

  • Yanjun Zhang
  • , Gang Tao*
  • , Mou Chen
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper presents a new study on adaptive output tracking control of multi-input multi-output (MIMO) T-S fuzzy system models in general non-canonical forms. Unlike canonical-form nonlinear systems whose T-S fuzzy system models have explicit relative degrees which can be directly used for deriving parametrized adaptive controllers, T-S fuzzy approximation models of non-canonical nonlinear systems generally have implicit relative degrees. For the design of adaptive feedback linearization based control to deal with system parameter uncertainties, the system dynamics of non-canonical form T-S fuzzy systems need to be reparametrized. This paper shows how to conduct a reparametrization based on relative degrees for general uncertain MIMO T-S fuzzy system models and how to derive feedback linearization based controller and its adaptive version which guarantees closed-loop stability and asymptotic output tracking. An illustrative example is presented to show the control design procedure and verify the effectiveness of the proposed control design method.

Original languageEnglish
Title of host publication54rd IEEE Conference on Decision and Control,CDC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6288-6293
Number of pages6
ISBN (Electronic)9781479978861
DOIs
Publication statusPublished - 8 Feb 2015
Externally publishedYes
Event54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan
Duration: 15 Dec 201518 Dec 2015

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume54rd IEEE Conference on Decision and Control,CDC 2015
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference54th IEEE Conference on Decision and Control, CDC 2015
Country/TerritoryJapan
CityOsaka
Period15/12/1518/12/15

Keywords

  • Adaptation models
  • Adaptive systems
  • Control design
  • Fuzzy systems
  • MIMO
  • Nonlinear systems

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