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    Please use this identifier to cite or link to this item: http://chur.chu.edu.tw/handle/987654321/33810


    Title: Adaptive TSK-type Self-evolving Neural Control for Unknown Nonlinear Systems
    Authors: 林友雄
    Lin, Yu-Hsiung
    Contributors: 電機工程學系
    Electrical Engineering
    Keywords: 適應性控制;類神經控制;TSK型類神經網路
    adaptive control;neural control;TSK-type neural network
    Date: 2012
    Issue Date: 2014-06-27 02:31:06 (UTC+8)
    Abstract: 本論文針對渾沌同步控制系統提出了一種新型的智慧型控制系統，所提出的控制系統包含一個類神經控制器與一個補償控制器。類神經控制器主要利用自進化TSK型類神經網路來實現，補償控制器利用克服類神經網路的學習誤差。最後，模擬結果充分顯示所提出適應性自進化TSK型類神經控制器之優越學習性能。
    In this paper, a real-time approximator using a
    TSK-type self-evolving neural network (TSNN) is studied. The
    learning algorithm of the proposed TSNN not only
    automatically online generates and prunes the hidden neurons
    but also online adjusts the netw
    Appears in Collections:[Department of Electrical Engineering] Seminar Papers

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