ROBUST STABILITY OF MARKOVIAN JUMPING GENETIC REGULATORY NETWORKS WITH DISTURBANCE ATTENUATION

被引：7
|
作者：
Yao, Yingtao [1 ]
Liang, Jinling [1 ]
Cao, Jinde [1 ]
机构：
[1] Southeast Univ, Dept Math, Nanjing 210096, Peoples R China
来源：
ASIAN JOURNAL OF CONTROL | 2011年 / 13卷 / 05期
基金：
中国国家自然科学基金;
关键词：
Genetic regulatory networks; stochastic perturbation; Lyapunov functional; linear matrix inequality; Markovian jumping; robust stability; H-INFINITY CONTROL; STOCHASTIC STABILITY; SYSTEMS; SYNCHRONIZATION; EXPRESSION; EQUATIONS; LOGIC; NOISE;
D O I：
10.1002/asjc.373
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Because of intracellular and extracellular noise perturbations and environment fluctuations, gene regulation is an intrinsically noisy process. In this paper, we present a hybrid genetic regulatory network (GRN) model which is based on the Markov chain. The GRNs are composed of N modes and the network switches from one mode to another according to a Markov chain with known transition probability. Time-delays here are mode-dependent. Based on the Lyapunov stability theory and the linear matrix inequality (LMI) technique, sufficient conditions are given to ensure the stochastic stability of the GRNs with polytopic uncertainties and disturbance attenuation. All the conditions are presented in terms of LMIs which are easily verified via the LMI toolbox. Examples are provided to illustrate the effectiveness of the theoretical results.
引用
收藏
页码：655 / 666
页数：12
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