Observer Design for Switched Recurrent Neural Networks: an Average Dwell Time Approach

被引：101

作者：

Lian, Jie ^{[1
]}

Feng, Zhi ^{[1
]}

Shi, Peng ^{[2
,3
,4
]}

机构：

[1] Dalian Univ Technol, Fac Elect Informat & Elect Engn, Dalian 116024, Peoples R China

[2] Univ Glamorgan, Dept Comp & Math Sci, Pontypridd CF37 1DL, M Glam, Wales

[3] Victoria Univ, Sch Sci & Engn, Melbourne, Vic 8001, Australia

[4] Univ S Australia, Sch Math & Stat, Adelaide, SA 5095, Australia

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 2011年 / 22卷 / 10期

基金：

美国国家科学基金会;

关键词：

Average dwell time method; exponential stability; observer design; switched neural networks; time-varying delay; EXPONENTIAL STABILITY ANALYSIS; DELAY-DEPENDENT STABILITY; H-INFINITY CONTROL; STATE ESTIMATION; LINEAR-SYSTEMS; ROBUST STABILITY; VARYING DELAY; DISCRETE; STABILIZATION;

D O I：

10.1109/TNN.2011.2162111

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper is concerned with the problem of observer design for switched recurrent neural networks with time-varying delay. The attention is focused on designing the full-order observers that guarantee the global exponential stability of the error dynamic system. Based on the average dwell time approach and the free-weighting matrix technique, delay-dependent sufficient conditions are developed for the solvability of such problem and formulated as linear matrix inequalities. The error-state decay estimate is also given. Then, the stability analysis problem for the switched recurrent neural networks can be covered as a special case of our results. Finally, four illustrative examples are provided to demonstrate the effectiveness and the superiority of the proposed methods.

引用

页码：1547 / 1556

页数：10

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