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
收藏
页码：720 / 726
页数：7
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