English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62379/95055 (66%)
Visitors : 2298075      Online Users : 173
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/75379

    Title: Design of a CMAC-based smooth adaptive neural controller with a saturation compensator
    Authors: Yen, Ming-ching;許駿飛;Hsu, Chun-fei;Chung, In-hang
    Contributors: 淡江大學電機工程學系暨研究所
    Keywords: Chua’s chaotic circuit;DC motor driver;CMAC neural network;Adaptive control;Neural control
    Date: 2012-02-01
    Issue Date: 2012-03-22 14:26:24 (UTC+8)
    Publisher: Springer London
    Abstract: 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.
    Relation: Neural Computing and Applications 12(1), pp.35-44
    DOI: 10.1007/s00521-011-0615-5
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

    Files in This Item:

    File Description SizeFormat
    paper.pdfpaper1163KbAdobe PDF499View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback