Optimal and stable fuzzy controllers for nonlinear systems based on an improved genetic algorithm

被引：36
|
作者：
Leung, FHF [1 ]
Lam, HK [1 ]
Ling, SH [1 ]
Tam, PKS [1 ]
机构：
[1] Hong Kong Polytech Univ, Ctr Multimedia Signal Proc, Dept Elect & Informat Engn, Kowloon, Hong Kong, Peoples R China
来源：
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2004年 / 51卷 / 01期
关键词：
fuzzy control; nonlinear systems; optimality and stability;
D O I：
10.1109/TIE.2003.821898
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper addresses the optimization and stabilization problems of nonlinear systems subject to parameter uncertainties. The methodology is based on a fuzzy logic approach and an improved genetic algorithm (GA). The TSK fuzzy plant model is employed to describe the dynamics of the uncertain nonlinear plant. A fuzzy controller is then obtained to close the feedback loop. The stability conditions are derived. The feedback gains of the fuzzy controller and the solution for meeting the stability conditions are determined using the improved GA. In order to obtain the optimal fuzzy controller, the membership functions are further tuned by minimizing a defined fitness function using the improved GA. An application example on stabilizing a two-link robot. arm will be given.
引用
收藏
页码：172 / 182
页数：11
相关论文
共 50 条
  • [1] Optimal and stable fuzzy controllers for nonlinear systems subject to parameter uncertainties using genetic algorithm
    Lam, HK
    Ling, SH
    Leung, FHF
    Tam, PKS
    10TH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-3: MEETING THE GRAND CHALLENGE: MACHINES THAT SERVE PEOPLE, 2001, : 908 - 911
  • [2] Genetic algorithm based fuzzy controller for nonlinear systems
    Jamshidifar, AA
    Lucas, C
    2004 2ND INTERNATIONAL IEEE CONFERENCE INTELLIGENT SYSTEMS, VOL 3, STUDENT SESSIONS, PROCEEDINGS, 2004, : 43 - 47
  • [3] Stable fuzzy controller design for uncertain nonlinear systems: Genetic algorithm approach
    Leung, FHF
    Lam, HK
    Tam, PKS
    Lee, YS
    PROCEEDINGS OF THE 12TH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1 AND 2, 2003, : 500 - 505
  • [4] Optimal H∞ Fuzzy Control for Nonlinear Interconnected Systems via Genetic Algorithm
    Hsiao, Feng-Hsiag
    Liu, Chien-Yu
    APPLIED MECHANICS AND MECHANICAL ENGINEERING IV, 2014, 459 : 256 - 261
  • [5] Research on Optimizing Fuzzy Controllers Based on Genetic Algorithm
    Xu, Kaijun
    Zhang, Chunyan
    Wang, Shuwang
    Zhang, Hannian
    2012 IEEE FIFTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI), 2012, : 545 - 548
  • [6] Improved Genetic Algorithm for Finite-Horizon Optimal Control of Nonlinear Systems
    Khamis, Ahmed
    Zydek, Dawid
    Selvaraj, Henry
    2017 25TH INTERNATIONAL CONFERENCE ON SYSTEMS ENGINEERING (ICSENG), 2017, : 85 - 90
  • [7] Improved genetic algorithm for optimal design of fuzzy classifier
    Kumar, P. Ganesh
    Devaraj, D.
    INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2009, 35 (2-4) : 97 - 103
  • [8] Genetic algorithm based methodology to generate automatically optimal fuzzy systems
    Rahmoun, A
    Benmohamed, M
    IEE PROCEEDINGS-CONTROL THEORY AND APPLICATIONS, 1998, 145 (06): : 583 - 586
  • [9] Automatic optimal design of fuzzy controllers based on genetic algorithms
    Osmera, P
    Matousek, R
    Stastny, J
    PROCEEDINGS OF THE THIRD NORDIC WORKSHOP ON GENETIC ALGORITHMS AND THEIR APPLICATIONS (3NWGA), 1997, : 265 - 274
  • [10] Learning rule structures of fuzzy controllers based on genetic algorithm
    Xiong, N.
    Systems Science, 2000, 26 (02): : 69 - 84
12345