H tracking-based sliding mode control for uncertain nonlinear systems via an adaptive fuzzy-neural approach

Wei Yen Wang*, Mei Lang Chan, Chen Chien James Hsu, 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

187 引文 斯高帕斯(Scopus)

摘要

In this paper, a novel adaptive fuzzy-neural sliding mode controller with H tracking performance for uncertain nonlinear systems is proposed to attenuate the effects caused by unmodeled dynamics, disturbances and approximate errors. Because of the advantages of fuzzy-neural systems, which can uniformly approximate nonlinear continuous functions to arbitrary accuracy, adaptive fuzzy-neural control theory is then employed to derive the update laws for approximating the uncertain nonlinear functions of the dynamical system. Furthermore, the H tracking design technique and the sliding mode control method are incorporated into the adaptive fuzzy-neural control scheme so that the derived controller is robust with respect to unmodeled dynamics, disturbances and approximate errors. Compared with conventional methods, the proposed approach not only assures closed-loop stability, but also guarantees an H tracking performance for the overall system based on a much relaxed assumption without prior knowledge on the upper bound of the lumped uncertainties. Simulation results have demonstrated that the effect of the lumped uncertainties on tracking error is efficiently attenuated, and chattering of the control input is significantly reduced by using the proposed approach.

原文英語
頁(從 - 到)483-492
頁數10
期刊IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
32
發行號4
DOIs
出版狀態已發佈 - 2002 8月
對外發佈

ASJC Scopus subject areas

  • 控制與系統工程
  • 軟體
  • 資訊系統
  • 人機介面
  • 電腦科學應用
  • 電氣與電子工程

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