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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/91655


    Title: Adaptive hermite-polynomial-based CMAC neural control for chaos synchronization
    Authors: Hsu, Chun-Fei
    Contributors: 淡江大學電機工程學系
    Keywords: Adaptive control;Neural control;CMAC neural network;Hermite polynomial
    Date: 2012-11
    Issue Date: 2013-07-23 21:57:11 (UTC+8)
    Abstract: Gyros are a particularly interesting form of nonlinear systems that have attracted many researchers due to their applications in the navigational, aeronautical and space engineering domains. In this paper, a problem of synchronization between two chaotic gyros based on a mater-slave scheme is studied. An adaptive
    Hermite-polynomial-based CMAC neural control (AHCNC) system which is composed of a neural controller and a smooth compensator is proposed. The neural controller using a Hermite-polynomial-based CMAC neural network (HCNN) is main controller and the smooth compensator is designed to guarantee system stable in the Lyapunov stability theorem. Finally, the simulation results show that the proposed AHCNC scheme can achieve favorable chaos synchronization after the controller parameters learning.
    Relation: Proceedings of 2012 CACS International Automatic Control Conference, 6p.
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Proceeding

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