New time-efficient structure for observer-based adaptive fuzzy-neural controllers for nonaffine nonlinear systems

Wei-Yen Wang, I. Hsum Li, Ming Chang Chen, Shun Feng Su, Yih-Guang Leu

    研究成果: 雜誌貢獻文章同行評審

    5 引文 斯高帕斯(Scopus)

    摘要

    This paper proposes an observer-based adaptive controller with a merged fuzzy-neural network for nonaffine nonlinear systems under the constraint that only the system output is available for measurement. Using a conventional fuzzy-neural network leads to rule explosion which leads to huge computation time. Our proposed merged-FNN does not have this problem, and can take the place of the conventional fuzzy-neural networks under some assumptions while maintaining the property of stability. Moreover, the adaptive scheme using the merged-FNN guarantees that all signals involved are bounded and the output of the closed-loop system asymptotically tracks the desired output trajectory. Finally, this paper gives examples of the proposed controller for nonaffine nonlinear systems, and is shown to provide good effectiveness.

    原文英語
    頁(從 - 到)963-978
    頁數16
    期刊International Journal of Innovative Computing, Information and Control
    6
    發行號3
    出版狀態已發佈 - 2010 三月 1

    ASJC Scopus subject areas

    • Software
    • Theoretical Computer Science
    • Information Systems
    • Computational Theory and Mathematics

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