淡江大學機構典藏:Item 987654321/112101
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62797/95867 (66%)
Visitors : 3740396      Online Users : 562
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/987654321/112101


    Title: Design of self-constructing fuzzy wavelet neural control system
    Authors: Tsu-Tian Lee, Po-Chun Wang, Chih-Ching Hsiao, and Chun-Fei Hsu
    Keywords: intelligent control;Lyapunov stability theory;fuzzy neural network;wavelet neural network;self construction
    Date: 2017-06-30
    Issue Date: 2017-11-15 02:10:34 (UTC+8)
    Publisher: IEEE
    Abstract: In this paper, a self-constructing fuzzy wavelet
    neural network (SFWNN) is used to approximate an unknown
    nonlinear term in the system dynamics with the structure and
    parameter learning abilities concurrently. Further, a selfconstructing
    fuzzy wavelet neural control (SFWNC) system,
    which is composed of a computation controller and a robust
    compensator, is proposed. The computation controller using the
    SFWNN approximator is the main controller and the robust
    compensator is designed to eliminate the effect of the
    approximation error. All controller parameters of the SFWNC
    system are adaptively update based on the Lyapunov stability
    theory and the projection algorithm to guarantee the closed-loop
    system stability. Finally, the effectiveness of the proposed
    SFWNC system is verified by simulation results and the SFWNN
    approximator has the admirable property of small fuzzy rules
    size and high learning accuracy.
    Relation: Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems
    DOI: 10.1109/IFSA-SCIS.2017.8023231
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Proceeding

    Files in This Item:

    There are no files associated with this item.

    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