Parameter estimation of fuzzy controller and its application to inverted pendulum

被引：51
|
作者：
Oh, SK
Pedrycz, W [1 ]
Rho, SB
Ahn, TC
机构：
[1] Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 2G6, Canada
[2] Polish Acad Sci, Syst Res Inst, PL-01447 Warsaw, Poland
[3] Wonkwang Univ, Sch Elect & Elect Engn, Iksan 570749, Chon Buk, South Korea
来源：
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2004年 / 17卷 / 01期
关键词：
fuzzy PID/PD controller; estimation algorithms; HCM (Hard C-Means); HCM clustering based regression polynomial; neuro-fuzzy networks (NFN) model;
D O I：
10.1016/j.engappai.2003.12.003
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a new approach to estimate scaling factors of the fuzzy PID controller is presented. The performance of the fuzzy PID controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing (more specifically, a genetic algorithm) and estimation algorithm. The tuning of the scaling factors of the fuzzy PID controller is essential to the entire optimization process. And then we estimate scaling factors of the fuzzy PID controller by means of three types of estimation algorithms such as HCM (Hard C-Means) clustering-based regression polynomial, neuro-fuzzy networks, and regression polynomials. Numerical studies are presented in detail along with a detailed comparative analysis. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码：37 / 60
页数：24
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