State estimation for Markovian jumping genetic regulatory networks with random delays

被引：20

作者：

Liu, Jinliang ^{[1
,2
]}

Tian, Engang ^{[3
]}

Gu, Zhou ^{[4
]}

Zhang, Yuanyuan ^{[1
]}

机构：

[1] Nanjing Univ Finance & Econ, Dept Appl Math, Nanjing 210023, Jiangsu, Peoples R China

[2] Southeast Univ, Sch Automat, Nanjing 210096, Jiangsu, Peoples R China

[3] Nanjing Normal Univ, Inst Informat & Control Engn Technol, Nanjing 210042, Jiangsu, Peoples R China

[4] Nanjing Forestry Univ, Coll Mech & Elect Engn, Nanjing 210042, Jiangsu, Peoples R China

来源：

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2014年 / 19卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Genetic regulatory networks; State estimation; Markovian jumping parameters; Time-varying delays; H-INFINITY CONTROL; ROBUST STABILITY; TIME; SYSTEMS; CRITERION;

D O I：

10.1016/j.cnsns.2013.11.002

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, the state estimation problem is investigated for stochastic genetic regulatory networks (GRNs) with random delays and Markovian jumping parameters. The delay considered is assumed to be satisfying a certain stochastic characteristic. Meantime, the delays of GRNs are described by a binary switching sequence satisfying a conditional probability distribution. The aim of this paper is to design a state estimator to estimate the true states of the considered GRNs through the available output measurements. By using Lyapunov functional and some stochastic analysis techniques, the stability criteria of the estimation error systems are obtained in the form of linear matrix inequalities under which the estimation error dynamics is globally asymptotically stable. Then, the explicit expression of the desired estimator is shown. Finally, a numerical example is presented to show the effectiveness of the proposed results. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：2479 / 2492

页数：14

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