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

研究成果: 雜誌貢獻文章

60 引文 斯高帕斯(Scopus)

摘要

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.

原文英語
文章編號5580106
頁(從 - 到)542-552
頁數11
期刊IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
41
發行號2
DOIs
出版狀態已發佈 - 2011 四月 1

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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