Less conservative delay-dependent H∞ control of uncertain neural networks with discrete interval and distributed time-varying delays

被引:49
|
作者
Ali, M. Syed [1 ]
Saravanakumar, R. [1 ]
Zhu, Quanxin [2 ,3 ]
机构
[1] Thiruvalluvar Univ, Dept Math, Vellore 632115, Tamil Nadu, India
[2] Nanjing Normal Univ, Sch Math Sci, Nanjing 210023, Jiangsu, Peoples R China
[3] Nanjing Normal Univ, Inst Finance & Stat, Nanjing 210023, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Distributed delay; Interval time-varying delay; Linear matrix inequality (LMI); Lyapunov method; Neural network; H-infinity control; STABILITY-CRITERIA; STATE ESTIMATION; EXPONENTIAL STABILITY; FUZZY-SYSTEMS; PARAMETERS;
D O I
10.1016/j.neucom.2015.04.023
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 deals with the robust H-infinity control problem for a class of uncertain neural networks with discrete interval and distributed time-varying delays. The main purpose of this paper is to estimate robust asymptotic stability of the given neural network with H-infinity performance analysis gamma. By constructing novel Lyapunov-Krasovskii functionals with triple integral terms, several new less conservative delay-dependent stability conditions for H-infinity control are obtained in terms of linear matrix inequalities. Numerical examples are given to illustrate the effectiveness of the proposed theoretical results. The method given in this paper shows less conservative results when comparing with some existing methods. (C) 2015 Elsevier B.V. All rights reserved.
引用
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页码:84 / 95
页数:12
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