Delay-Dependent Stability Analysis for Switched Neural Networks With Time-Varying Delay

被引：182
|
作者：
Wu, Zheng-Guang [1 ]
Shi, Peng [2 ,3 ,4 ]
Su, Hongye [1 ]
Chu, Jian [1 ]
机构：
[1] Zhejiang Univ, Natl Lab Ind Control Technol, Inst Cyber Syst & Control, Hangzhou 310027, Zhejiang, Peoples R China
[2] Univ Glamorgan, Fac Adv Technol, Pontypridd CF37 1DL, M Glam, Wales
[3] Univ S Australia, Sch Math & Stat, Mawson Lakes, SA 5095, Australia
[4] Victoria Univ, Sch Engn & Sci, Melbourne, Vic 8001, Australia
来源：
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS | 2011年 / 41卷 / 06期
基金：
国家高技术研究发展计划(863计划);
关键词：
Exponential stability; linear matrix inequality (LMI); neural networks; switched systems; time-varying delay; ROBUST EXPONENTIAL STABILITY; GLOBAL ASYMPTOTIC STABILITY; POLYTOPIC LINEAR-SYSTEMS; ADAPTIVE-CONTROL; DISCRETE; CRITERIA;
D O I：
10.1109/TSMCB.2011.2157140
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, the problem of stability analysis is investigated for switched neural networks with time-varying delay using linear matrix inequality (LMI) approach. By taking advantage of the average dwell time method, two sufficient conditions are developed to ensure the global exponential stability of the considered neural networks, which are delay-dependent and formulated by LMIs. The state decay estimate is explicitly given. Numerical examples are provided to demonstrate the effectiveness and feasibility of the proposed techniques.
引用
收藏
页码：1522 / 1530
页数：9
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