淡江大學機構典藏:Item 987654321/53575
English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 62805/95882 (66%)
造訪人次 : 3934183      線上人數 : 539
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/53575


    題名: A Stable Self-Learning Optimal Fuzzy Control System
    作者: Lin, Sinn-cheng;Chen, Yung-yaw
    貢獻者: 淡江大學資訊與圖書館學系
    關鍵詞: Fuzzy control;Optimal control;Fuzzy sliding mode control;Genetic algorithms
    日期: 1999-09-01
    上傳時間: 2011-05-20 09:48:15 (UTC+8)
    出版者: Wiley
    摘要: The issue of developing a stable self-learning optimal fuzzy control system is discussed in this paper. Three chief objectives are accomplished: 1) To develop a self-learning fuzzy controller based on genetic algorithms. In the proposed methodology, the concept of a fuzzy sliding mode is introduced to specify the system response, to simplify the fuzzy rules and to shorten the chromosome length. The speed of fuzzy inference and genetic evolution of the proposed strategy, consequently, is higher than that of the conventional fuzzy logic control. 2) To guarantee the stability of the learning control system. A hitting controller is designed to achieve this requirement. It works as an auxiliary controller and supports the self-learning fuzzy controller in the following manner. When the learning controller works well enough to allow the system state to lie inside a pre-defined boundary layer, the hitting controller is disabled. On the other hand, if the system tends to diverge, the hitting controller is turned on to pull the state back. The system is therefore stable in the sense that the state is bounded by the boundary layer. 3) To explore a fuzzy rule-base that can minimize a standard quadratic cost function. Based on the fuzzy sliding regime, the problem of minimizing the quadratic cost function can be transformed into that of deriving an optimal sliding surface. Consequently, the proposed learning scheme is directly applied to extract the optimal fuzzy rulebase. That is, the faster the hitting time a controller has and the shorter the distance from the sliding surface the higher fitness it possesses. The superiority of the proposed approach is verified through simulations.
    關聯: Asian Journal of Control 1(3), pp.169-177
    DOI: 10.1111/j.1934-6093.1999.tb00017.x
    顯示於類別:[資訊與圖書館學系暨研究所] 期刊論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    A STABLE SELF‐LEARNING OPTIMAL FUZZY CONTROL SYSTEM.pdf94KbAdobe PDF2檢視/開啟
    index.html0KbHTML154檢視/開啟

    在機構典藏中所有的資料項目都受到原著作權保護.

    TAIR相關文章

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