A TSK-Type fuzzy neural network (TFNN) systems for dynamic systems identification

被引：0

作者：

Lee, CH ^{[1
]}

Lai, WY ^{[1
]}

Lin, YC ^{[1
]}

机构：

[1] Yuan Ze Univ, Dept Elect Engn, Chungli 320, Taoyuan, Taiwan

来源：

42ND IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-6, PROCEEDINGS | 2003年

关键词：

fuzzy neural network; TSK-type fuzzy systems; back-propagation algorithm; system identification;

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：

In this paper, a TSK-type fuzzy neural network system (TFNN) for identifying unknown dynamic systems is proposed. The TFNN system can learn its knowledge base from input-output training data. Thus, the unknown system is represented as several if-then rules with TSK-type consequent parts. The TFNN system can be randomly initialized and then trained by the back-propagation algorithm. Several examples are presented to illustrate the effectiveness of our approach.

引用

页码：4002 / 4007

页数：6

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