Observer-based direct adaptive fuzzy-neural control for nonaffine nonlinear systems

Yih Guang Leu*, Wei Yen Wang, Tsu Tian Lee

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

217 引文 斯高帕斯(Scopus)

摘要

In this paper, an observer-based direct adaptive fuzzy-neural control scheme is presented for nonaffine nonlinear systems in the presence of unknown structure of nonlinearities. A direct adaptive fuzzy-neural controller and a class of generalized nonlinear systems, which are called nonaffine nonlinear systems, are instead of the indirect one and affine nonlinear systems given by Leu et al. By using implicit function theorem and Taylor series expansion, the observer-based control law and the weight update law of the fuzzy-neural controller are derived for the nonaffine nonlinear systems. Based on strictly-positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be verified. Moreover, the overall adaptive scheme guarantees that all signals involved are bounded and the output of the closed-loop system will asymptotically track the desired output trajectory. To demonstrate the effectiveness of the proposed method, simulation results are illustrated in this paper.

原文英語
頁(從 - 到)853-861
頁數9
期刊IEEE Transactions on Neural Networks
16
發行號4
DOIs
出版狀態已發佈 - 2005 七月

ASJC Scopus subject areas

  • 軟體
  • 電腦科學應用
  • 電腦網路與通信
  • 人工智慧

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