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Exponential H ∞ filtering for switched stochastic genetic regulatory networks with random sensor delays
Author(s) -
Zhang Dan,
Yu Li,
Wang QingGuo
Publication year - 2011
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.330
Subject(s) - dwell time , control theory (sociology) , filter (signal processing) , filtering problem , exponential function , mathematics , exponential stability , exponential growth , set (abstract data type) , attenuation , class (philosophy) , genetic algorithm , mathematical optimization , computer science , control (management) , filter design , nonlinear system , mathematical analysis , physics , artificial intelligence , medicine , clinical psychology , quantum mechanics , optics , computer vision , programming language
Abstract The exponential H ∞ filtering problem is investigated in this paper for a class of switching‐type stochastic genetic regulatory networks (GRNs) with random sensor delays. The objective is to estimate the true concentrations of the mRNA and protein in the presence of random sensor delays. By using the average dwell time approach, sufficient conditions are derived to ensure the filtering error dynamics are mean‐square exponentially stable with a prescribed H ∞ disturbance attenuation level. The filter gains are given in terms of the solution to a set of linear matrix inequalities (LMIs). A numerical example is presented to illustrate the effectiveness of the proposed design method. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society