Robust stability analysis for discrete-time genetic regulatory networks with probabilistic time delays

被引:17
|
作者
Wan, Xiongbo [1 ,2 ]
Xu, Li [2 ]
Fang, Huajing [3 ]
Yang, Fang [1 ]
机构
[1] Huazhong Agr Univ, Coll Engn, Wuhan 430070, Peoples R China
[2] Akita Prefectural Univ, Dept Elect & Informat Syst, Honjo, Akita 0150055, Japan
[3] Huazhong Univ Sci & Technol, Dept Control Sci & Engn, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Genetic regulatory networks (GRNs); Probabilistic time delays; Linear matrix inequalities (LMIs); Asymptotically mean-square stable; CONTROL-SYSTEMS; VARYING DELAY; H-INFINITY;
D O I
10.1016/j.neucom.2013.07.037
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 investigates the robust stability problem of a class of discrete-time genetic regulatory networks (GRNs) with probabilistic time delays. Different from the previous works, at each instant the feedback regulation delay and the translation delay are assumed to take values in two given finite sets with deterministic probability distributions. By utilizing a class of indicator functions and discrete-time Jensen inequality, delay-probability-distribution-dependent sufficient conditions are obtained in terms of linear matrix inequalities (LMIs) such that the discrete-time GRNs are robustly asymptotically stable in the mean-square sense for all admissible uncertainties and random delays. Three numerical examples are given to demonstrate the effectiveness of our theoretical results. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:72 / 80
页数:9
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