English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 94201/94201 (100%)
造訪人次 : 81536646      線上人數 : 2301
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU 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://ir.lib.ncu.edu.tw/handle/987654321/106803


    題名: Computed force control system using functional link radial basis function network with asymmetric membership function for piezo-flexural nanopositioning stage
    作者: 林法正;Lin, Faa-Jeng;Lee, Shih-Yang;Chou, Po-Huan
    貢獻者: 資訊電機學院電機工程學系
    關鍵詞: adaptive control;adaptive learning algorithms;asymmetric membership function;auxiliary control;Computation;computed force control system;dynamic characteristics;equivalent hysteresis friction force;FLRBFN‐AMF;force control;functional link radial basis function network;fuzzy rules;fuzzy set theory;improved steady‐state response;learning systems;lumped uncertainty;Lyapunov methods;Lyapunov stability theorem;motion control;nanopositioning;neurocontrollers;nonlinear control systems;nonlinear system;PFNS mechanism;piezo‐flexural nanopositioning stage;radial basis function networks;reference contours;reference trajectories;stability;three‐dimension motion control;time varying system;time‐varying systems
    日期: 2013-11-25
    上傳時間: 2026-04-23 13:43:44 (UTC+8)
    出版者: Institution of Engineering and Technology;Stevenage: The Institution of Engineering and Technology
    摘要: 摘要: A computed force control system using functional link radial basis function network with asymmetric membership function (FLRBFN-AMF) for three-dimension motion control of a piezo-flexural nanopositioning stage (PFNS) is proposed in this study. First, the dynamics of the PFNS mechanism with the introduction of a lumped uncertainty including the equivalent hysteresis friction force are derived. Then, a computed force control system with an auxiliary control is proposed for the tracking of the reference contours with improved steady-state response. Since the dynamic characteristics of the PFNS are non-linear and time varying, a computed force control system using FLRBFN-AMF is designed to improve the control performance for the tracking of various reference trajectories, where the FLRBFN-AMF is employed to estimate a non-linear function including the lumped uncertainty of the PFNS. Moreover, by using the asymmetric membership function, the learning capability of the networks can be upgraded and the number of fuzzy rules can be optimised for the functional link radial basis function network. Furthermore, the adaptive learning algorithms for the training of the parameters of the FLRBFN-AMF online are derived using the Lyapunov stability theorem. Finally, some experimental results for the tracking of various reference contours of the PFNS are given to demonstrate the validity of the proposed control system.
    出版者: Stevenage: The Institution of Engineering and Technology
    出版日期: 2013-12
    出處: IET control theory & applications, 2013-12, Vol.7 (18), p.2128-2142
    資源來源: Wiley Online Library Open Access
    版權: The Institution of Engineering and Technology
    版權: 2021 The Authors. IET Control Theory & Applications published by John Wiley & Sons, Ltd. on behalf of The Institution of Engineering and Technology
    版權: Copyright The Institution of Engineering & Technology Dec 2013
    識別號: ISSN: 1751-8644
    識別號: ISSN: 1751-8652
    識別號: EISSN: 1751-8652
    識別號: DOI: 10.1049/iet-cta.2013.0086
    顯示於類別:[電機工程學系] 期刊論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML19檢視/開啟


    在NCUIR中所有的資料項目都受到原著作權保護.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明