Stability analysis of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays

被引：50

作者：

Hou, Yi-You ^{[1
]}

Liao, Teh-Lu

Yan, Jun-Juh

机构：

[1] Natl Cheng Kung Univ, Dept Engn Sci, Tainan 70101, Taiwan

[2] Shu Te Univ, Dept Comp & Commun, Kaohsiung 824, Taiwan

来源：

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS | 2007年 / 37卷 / 03期

关键词：

cellular neural networks (CNNs); linear matrix inequality (LMI); Lyapunov-Krasovskii functional theory; Takagi-Sugeno (T-S) fuzzy model; time-varying delay;

D O I：

10.1109/TSMCB.2006.889628

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This correspondence investigates the global exponential stability problem of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays (TSFDCNNs). Based on the Lyapunov-Krasovskii functional theory and linear matrix inequality technique, a less conservative delay-dependent stability criterion is derived to guarantee the exponential stability of TSFDCNNs. By constructing a Lyapunov-Krasovskii functional, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is released in the proposed delay-dependent stability criterion. Two illustrative examples are provided to verify the effectiveness of the proposed results.

引用

页码：720 / 726

页数：7

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