淡江大學機構典藏:Item 987654321/75379
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    题名: Design of a CMAC-based smooth adaptive neural controller with a saturation compensator
    作者: Yen, Ming-ching;許駿飛;Hsu, Chun-fei;Chung, In-hang
    贡献者: 淡江大學電機工程學系暨研究所
    关键词: Chua’s chaotic circuit;DC motor driver;CMAC neural network;Adaptive control;Neural control
    日期: 2012-02-01
    上传时间: 2012-03-22 14:26:24 (UTC+8)
    出版者: Springer London
    摘要: In the conventional CMAC-based adaptive controller design, a switching compensator is designed to guarantee system stability
    in the Lyapunov stability sense but the undesirable chattering phenomenon occurs. This paper proposes a CMAC-based smooth
    adaptive neural control (CSANC) system that is composed of a neural controller and a saturation compensator. The neural controller
    uses a CMAC neural network to online mimic an ideal controller and the saturation compensator is designed to dispel the approximation
    error between the ideal controller and neural controller without any chattering phenomena. The parameter adaptive algorithms
    of the CSANC system are derived in the sense of Lyapunov stability, so the system stability can be guaranteed. Finally, the
    proposed CSANC system is applied to a Chua’s chaotic circuit and a DC motor driver. Simulation and experimental results show
    the CSANC system can achieve a favorable tracking performance. It should be emphasized that the development of the proposed
    CSANC system doesn’t need the knowledge of the system dynamics.
    關聯: Neural Computing and Applications 12(1), pp.35-44
    DOI: 10.1007/s00521-011-0615-5
    显示于类别:[電機工程學系暨研究所] 期刊論文

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