Self learning fuzzy controllers using iterative learning tuner

被引:0
|
作者
Ashraf, Suhail [1 ]
Muhammad, Ejaz [1 ]
Al-Habaibeh, Amin [2 ]
Rashid, Farooq
机构
[1] Natl Univ Sci & Technol, Dept Elect Engn, Rawalpindi, Pakistan
[2] Nottingham Trent Univ, Adv Design Mfg Engn Ctr, Nottingham, England
关键词
Fuzzy control; Learning control; Adaptive control; Iterative learning; SYSTEMS; COMPLEX; ROBOT;
D O I
10.1016/j.dsp.2009.06.004
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper describes the design of an adaptive fuzzy controller using iterative learning to tune input membership functions and scaling factor(s). The control scheme consists of a fuzzy controller and learning control laws. People's perception about the meaning of a linguistic variable differs from person to person or even from expert to expert. This difference in perception usually leads to different fuzzy control designs. Some where within these designs lays the required design which meets a specific performance criterion. This paper proposes an approach to tackle this uncertainty in perception, to find the required design using membership function modification. The membership function is adaptively adjusted through iterative learning technique. The results show that the scheme is robust, cost effective and very simple to implement. It makes use of the nonlinearity inherent in the fuzzy systems. This scheme can be used to design fuzzy controllers for different plants by finding the right membership functions to ensure the required design specifications. Designing fuzzy controllers with desired performance specifications is not a trivial task. Even the specification of linguistic variables, key concept in fuzzy system design, can be different from different experts. This scheme tries to fill this gap. Adaptive fuzzy techniques are computationally heavy to implement. The proposed scheme lays out a unique adaptive procedure for designing fuzzy controllers through iterative learning process. (C) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:289 / 300
页数:12
相关论文
共 50 条
  • [41] Development of a multivariable test facility for the evaluation of iterative learning controllers
    Thanh Dinh
    Freeman, Chris
    Lewin, Paul
    2012 AMERICAN CONTROL CONFERENCE (ACC), 2012, : 621 - 626
  • [42] Framework for Implementation of Iterative Learning Control on Programmable Logic Controllers
    Bibl, Matthias
    Robin, Michael
    Steinegger, Michael
    Schitter, Georg
    2016 IEEE 21ST INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA), 2016,
  • [43] Experience-Based Iterative Learning Controllers for Robotic Systems
    M. Arif
    T. Ishihara
    H. Inooka
    Journal of Intelligent and Robotic Systems, 2002, 35 : 381 - 396
  • [44] Fuzzy adaptive iterative learning control algorithm
    Wang, Yan
    Fu, Yongling
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 3719 - +
  • [45] Fuzzy Iterative Learning Control of Servo System
    Liu, Hongli
    Zhu, Qixin
    Chen, Xiangwen
    HIGH PERFORMANCE STRUCTURES AND MATERIALS ENGINEERING, PTS 1 AND 2, 2011, 217-218 : 917 - +
  • [46] Repetitive Process based Design of Dynamic Iterative Learning Controllers
    Maniarski, Robert
    Paszke, Wojciech
    Rogers, Eric
    5TH IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (IEEE CCTA 2021), 2021, : 950 - 955
  • [47] A New Reinforcement Learning Method for Fuzzy Logic Controllers
    王直杰
    方建安
    邵世煌
    Journal of China Textile University(English Edition), 1998, (02) : 42 - 45
  • [48] An approach to tune fuzzy controllers based on reinforcement learning
    Dai, XH
    Li, CK
    Rad, AB
    PROCEEDINGS OF THE 12TH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1 AND 2, 2003, : 517 - 522
  • [49] Learning fuzzy controllers in mobile robotics with embedded preprocessing
    Rodriguez-Fdez, I.
    Mucientes, M.
    Bugarin, A.
    APPLIED SOFT COMPUTING, 2015, 26 : 123 - 142
  • [50] New reinforcement learning method for fuzzy logic controllers
    Wang, Zhijie
    Fang, Jian'an
    Shao, Shihuang
    Journal of Dong Hua University (English Edition), 1998, 15 (02): : 42 - 45