Process control using a CFCM-based on-line adaptive neuro-fuzzy systems

被引：0

作者：

Kwak, KC ^{[1
]}

Lee, DJ ^{[1
]}

Kim, SS ^{[1
]}

Ryu, JW ^{[1
]}

机构：

[1] Chungbuk Natl Univ, Dept Elect Engn, Seoul, South Korea

来源：

ISIE 2001: IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS PROCEEDINGS, VOLS I-III | 2001年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A conditional fuzzy c-means(CFCM)-based fuzzy adaptive neuro-fuzzy system(ANFS) by on-line teaming is proposed in this paper. In the structure identification, the optimal or near optimal number of fuzzy rules is determined by a CFCM clustering with TSK-type fuzzy rules based on the criterion, In the parameter identification, The consequent parameters are tuned by least squares estimator (LSE) and the premise parameters are tuned by back-propagation algorithm in off-line teaming. and then use on-line teaming by recursive least squares estimator (RLSE) and back-propagation algorithm to cope with time varying plant dynamics. Finally, we will show its capability for a CFCM-based on-line ANFS to control the temperature of a water path.

引用

页码：1244 / 1247

页数：4

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