Full Text:   <2292>

CLC number: TP183

On-line Access: 

Received: 1998-12-26

Revision Accepted: 1999-12-15

Crosschecked: 0000-00-00

Cited: 0

Clicked: 4760

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
1. Reference List
Open peer comments

Journal of Zhejiang University SCIENCE A 2000 Vol.1 No.3 P.311-316

http://doi.org/10.1631/jzus.2000.0311


A RAPID FUZZY RULE EXTRACTION METHOD FOR FUZZY CONTROLLER


Author(s):  YANG Jian-gang, WANG Ru-ming

Affiliation(s):  Dept.of Computer Science, Zhejiang University, Hangzhou, 310027, China

Corresponding email(s): 

Key Words:  fuzzy control, rule extraction, space division, sample reappearance


Share this article to: More

YANG Jian-gang, WANG Ru-ming. A RAPID FUZZY RULE EXTRACTION METHOD FOR FUZZY CONTROLLER[J]. Journal of Zhejiang University Science A, 2000, 1(3): 311-316.

@article{title="A RAPID FUZZY RULE EXTRACTION METHOD FOR FUZZY CONTROLLER",
author="YANG Jian-gang, WANG Ru-ming",
journal="Journal of Zhejiang University Science A",
volume="1",
number="3",
pages="311-316",
year="2000",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2000.0311"
}

%0 Journal Article
%T A RAPID FUZZY RULE EXTRACTION METHOD FOR FUZZY CONTROLLER
%A YANG Jian-gang
%A WANG Ru-ming
%J Journal of Zhejiang University SCIENCE A
%V 1
%N 3
%P 311-316
%@ 1869-1951
%D 2000
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2000.0311

TY - JOUR
T1 - A RAPID FUZZY RULE EXTRACTION METHOD FOR FUZZY CONTROLLER
A1 - YANG Jian-gang
A1 - WANG Ru-ming
J0 - Journal of Zhejiang University Science A
VL - 1
IS - 3
SP - 311
EP - 316
%@ 1869-1951
Y1 - 2000
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2000.0311


Abstract: 
Based on division of the three-dimensional space from data samples, the method proposed in this paper can rapidly extract fuzzy rules by using the fuzzy information of the samples. The principle of this approach is proved theoretically. Due to its simplicity this method can be used to extract fuzzy rules in real-time for an adaptive control system. Simulation results showed that this approach is effective and practical.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Yang Yupu, 1994. Extraction of fuzzy rules by using F-NN and the confidence interval estimation. Pattern Recognition & Artificial Intelligence, 7:53-59

[2]Li Gechen, 1997. A fuzzy controller based on new type neural network. Proc. of Fifith Robot Conference of China, Ha'erbing, p.461-466.

[3]Keller J.M., 1992. Neural network implementation of fuzzy logic. Fuzzy Set and System, 45(1):1-12.

[4]Park Y.M., 1996. An optimal tracking neuro-controller for nonlinear dynamic system.IEEE Trans on Neural Networks,7(5):1099-1110.

[5]Yang Jiangang, 1993. Real time dynamic control of a doubly inverted pendulum using ameliorated CMAC network: The 1st Congress of Post-Doctoral of China, National Defense Industry Press, Beijing, p.358-361.

[6]Jiao Licheng, 1993. Application and implementatioin of neural network. Xidian Press, Xi'an, 580 p.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE