DocumentCode
3550387
Title
Research on fuzzy modeling based on modified fuzzy clustering and its application
Author
Zongyi, Xing ; Weili, Hu ; Qingwei, Chen ; Limin, Jia
Author_Institution
Dept. of Autom., NanJing Univ. of Sci. & Technol., Jiangsu, China
Volume
3
fYear
2004
fDate
6-9 Dec. 2004
Firstpage
2292
Abstract
A new method of fuzzy modeling based on T-S fuzzy model is presented. In this approach, a modified fuzzy clustering algorithm is combined with the least square approximation method to identify the structure and parameters of the fuzzy model from a set of data. An L-M technique is used to optimize initial fuzzy model. The proposed method is applied to coke-oven temperature system, and the simulation results demonstrate its effectiveness.
Keywords
fuzzy control; fuzzy set theory; least squares approximations; modelling; pattern clustering; temperature control; L-M technique; T-S fuzzy model; coke-oven temperature; fuzzy modeling; least square approximation; modified fuzzy clustering; Automation; Clustering algorithms; Clustering methods; Fuzzy sets; Fuzzy systems; Genetic algorithms; Least squares approximation; Partitioning algorithms; Rail transportation; Temperature;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation, Robotics and Vision Conference, 2004. ICARCV 2004 8th
Print_ISBN
0-7803-8653-1
Type
conf
DOI
10.1109/ICARCV.2004.1469789
Filename
1469789
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