A Sampled-data Approach to Robust H∞ State Estimation for Genetic Regulatory Networks with Random Delays
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This paper is concerned with the robust H∞ state estimation problem for a class of uncertain genetic regulatory networks (GRNs) with random delays and external disturbances by using sample-data method. An important feature of this paper is that the time-varying delays are assumed to be random and their probability distributions are known a priori. By substituting the continuous measurements, the sampled measurements are used to estimate the concentrations of mRNAs and proteins. On the basis of the extended Wirtinger inequality, a discontinuous Lyapunov functional is introduced. Then, some sufficient conditions are derived in terms of a set of linear matrix inequalities (LMIs), which ensure that the error system is globally asymptotically stable in the meansquare sense and satisfies H∞ performance. Further, the explicit expression of the required estimator gain matrices is proposed. Finally, a numerical example is used to illustrate the effectiveness and feasibility of the obtained estimation method.
KeywordsDiscontinuous Lyapunov functional genetic regulatory networks random delays sampled-data approach state estimation
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- R. Yan and J. Liu, “New results on asymptotic and robust stability of genetic regulatory networks with time-varying delays,” International Journal of Innovation Computing Information and Control, vol. 8, no. 4, pp. 2889–2900, April 2012.Google Scholar
- C. H. Yuh, H. Bolouri, and E. H. Davidson, “Genomic cis-regulatory logic: experimental and computational analysis of a sea urchin gene,” Science Magazine, vol. 279, no. 5358, pp. 1896–1902, March 1998.Google Scholar
- J. Hu, Z. Wang, H. Gao, and L. K. Stergioulas, “Robust sliding mode control for discrete stochastic systems with mixed time-delays, randomly occurring uncertainties and randomly occurring nonlinearities,” IEEE Trans. on Industrial Electronics, vol. 59, no. 7, pp. 3008–3015, July 2012. [click]CrossRefGoogle Scholar
- Y. Tang, X. Xing, H. R. Karimi, L. Kocarev, and J. Kurths, “Tracking control of networked multi-agent systems under new characterizations of impulses and its applications in robotic systems,” IEEE Trans. on Industrial Electronics, vol. 63, no. 2, pp. 1299–1307, February 2016. [click]CrossRefGoogle Scholar