Design of state estimator for genetic regulatory networks with time-varying delays and randomly occurring uncertainties
- Design of state estimator for genetic regulatory networks with time-varying delays and randomly occurring uncertainties
- 박주현; 락쉬마난; 정호열; P. Balasubramaniam[P. Balasubramaniam]; S.M. Lee[S.M. Lee]
- MARKOVIAN JUMPING PARAMETERS; RECURRENT NEURAL-NETWORKS; ROBUST STABILITY ANALYSIS; H-INFINITY CONTROL; STOCHASTIC STABILITY; DISTRIBUTED DELAYS; DISCRETE; SYSTEMS; LOGIC
- Issue Date
- ELSEVIER SCI LTD
- BIOSYSTEMS, v.111, no.1, pp.51 - 70
- In this paper, the design problem of state estimator for genetic regulatory networks with time delays and randomly occurring uncertainties has been addressed by a delay decomposition approach. The norm-bounded uncertainties enter into the genetic regulatory networks (GRNs) in random ways, and such randomly occurring uncertainties (ROUs) obey certain mutually uncorrelated Bernoulli distributed white noise sequences. Under these circumstances, the state estimator is designed to estimate the true concentration of the mRNA and the protein of the uncertain GRNs. Delay-dependent stability criteria are obtained in terms of linear matrix inequalities by constructing a Lyapunov-Krasovskii functional and using some inequality techniques (LMIs). Then, the desired state estimator, which can ensure the estimation error dynamics to be globally asymptotically robustly stochastically stable, is designed from the solutions of LMIs. Finally, a numerical example is provided to demonstrate the feasibility of the proposed estimation schemes. (C) 2012 Elsevier Ireland Ltd. All rights reserved.
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