Robust adaptive controller design for a class of uncertain nonlinear systems using online T-S fuzzy-neural modeling approach

Yi Hsing Chien, Wei-Yen Wang, Yih-Guang Leu, Tsu Tian Lee

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58 Citations (Scopus)

Abstract

This paper proposes a novel method of online modeling and control via the TakagiSugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.

Original languageEnglish
Article number5580106
Pages (from-to)542-552
Number of pages11
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume41
Issue number2
DOIs
Publication statusPublished - 2011 Apr 1

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Online Systems
User-Computer Interface
Nonlinear systems
Uncertain systems
Closed loop systems
Controllers
Fuzzy control
Trajectories

Keywords

  • Fuzzy-neural model
  • online modeling
  • robust adaptive control
  • uncertain nonlinear systems

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Medicine(all)
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

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