Stable indirect adaptive control based on discrete-time T–S fuzzy model

R Qi, Mieczyslaw Brdys

Research output: Contribution to journalArticle

61 Citations (Scopus)


This paper presents an indirect adaptive fuzzy control scheme for uncertain nonlinear asymptotically stable plants. A discrete-time T-S fuzzy input-output model is employed to approximate the unknown plant dynamics. The T-S fuzzy model is fed with its own states, which are indeed its past outputs, rather than the measurements from the plants. Entirely based on this model, a feedback linearization control law is designed by using the model structure, model parameters and model states and then applied to control the model and the plant. Premise and consequent parameters of the model are updated on-line by gradient descent algorithm and recursive least square estimation method using plant output measurements. Stability analysis shows that if there the model structure is accurate the adaptive controller achieves the bounded tracking error and boundedness of all the closed-loop signals. In the ideal case where the signals are persistently exciting during the model parameter adaptation a perfect asymptotic tracking is ensured. The effectiveness of the method is verified by simulation application to SISO and MIMO example plants. (C) 2007 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)900-925
Number of pages26
JournalFuzzy Sets and Systems
Publication statusPublished - 16 Apr 2008


  • nonlinear adaptive control
  • stability
  • fuzzy control
  • T-S fuzzy model


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