Constructing nonlinear variable gain controllers via the Takagi-Sugeno fuzzy control

被引:79
|
作者
Ying, H [1 ]
机构
[1] Univ Texas, Med Branch, Dept Physiol & Biophys, Ctr Biomed Engn, Galveston, TX 77555 USA
关键词
fuzzy control; fuzzy controller design; fuzzy systems; nonlinear control; PID control; stability; Takagi-Sugeno fuzzy control; variable gain control;
D O I
10.1109/91.669021
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We investigated analytical structure of the Takagi-Sugeno (TS) type of fuzzy controllers, which was unavailable in the Literature. The TS fuzzy controllers we studied employ a new and simplified TS control rule scheme in which all the rule consequent use a common function and are proportional to one another, greatly reducing the number of parameters needed in the rules. Other components of the fuzzy controllers are general: arbitrary input fuzzy sets, any type of fuzzy logic, and the generalized defuzzifer, which contains the popular centroid defuzzifier as a special case. We proved that all these TS fuzzy controllers were nonlinear variable gain controllers and characteristics of the gain variation were parametrized and governed by the rule proportionality. We conducted an in-depth analysis on a class of nonlinear variable gain proportional-derivative (PD) controllers. We present the results to show: 1) how to analyze the characteristics of the variable gains in the contest of control; 2) why the nonlinear variable gain PD controllers can outperform their linear counterpart; and 3) how to generate various gain variation characteristics through the manipulation of the rule proportionality.
引用
收藏
页码:226 / 234
页数:9
相关论文
共 50 条
  • [1] The Takagi-Sugeno fuzzy controllers using the simplified linear control rules are nonlinear variable gain controllers
    Ying, H
    AUTOMATICA, 1998, 34 (02) : 157 - 167
  • [2] FUZZY PID CONTROL VIA MODIFIED TAKAGI-SUGENO RULES
    Mohan, B. M.
    INTELLIGENT AUTOMATION AND SOFT COMPUTING, 2011, 17 (02) : 165 - 174
  • [3] Stabilization of a Quadrotor via Takagi-Sugeno Fuzzy Control
    Jurado, Francisco
    Castillo-Toledo, B.
    Di Gennaro, S.
    WMSCI 2008: 12TH WORLD MULTI-CONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL III, PROCEEDINGS, 2008, : 168 - +
  • [4] An analytical study on structure, stability and design of general nonlinear Takagi-Sugeno fuzzy control systems
    Ying, H
    AUTOMATICA, 1998, 34 (12) : 1617 - 1623
  • [5] Nonlinear System H∞ Fuzzy Control within Takagi-Sugeno Framework
    Filasova, A.
    Hladky, V.
    Krokavec, D.
    2013 INTERNATIONAL CONFERENCE ON PROCESS CONTROL (PC), 2013, : 13 - 18
  • [6] Control Design of Nonlinear Networked Control Systems via Takagi-Sugeno Fuzzy Model
    Yoneyama, Jun
    2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI), 2017, : 1920 - 1926
  • [7] Takagi-Sugeno Fuzzy Nonlinear Control System for Optical Interferometry
    Coradini, Murilo Franco
    Felao, Luiz Henrique Vitti
    Lyra, Stephany de Souza
    Teixeira, Marcelo Carvalho Minhoto
    Kitano, Claudio
    SENSORS, 2025, 25 (06)
  • [8] Stability Analysis of Nonlinear Networked Control Systems via Takagi-Sugeno Fuzzy Model
    Yoneyama, Jun
    IFAC PAPERSONLINE, 2017, 50 (01): : 2989 - 2994
  • [9] Fuzzy Fault Tolerant Control via Takagi-Sugeno Fuzzy Models for Nonlinear Systems with Multiplicative Noises
    Chang, Wen-Jer
    Tsai, Yue-Syuan
    Ku, Cheung-Chieh
    INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2014, 16 (03) : 338 - 349
  • [10] Distributed Control of Networked Nonlinear Systems via Interconnected Takagi-Sugeno Fuzzy Systems With Nonlinear Consequent
    Araujo, Rodrigo Farias
    Torres, Leonardo A. B.
    Palhares, Reinaldo Martinez
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (08): : 4858 - 4867