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Robust Passivity Analysis of Stochastic Genetic Regulatory Networks with Levy Noise

Palraj Jothiappan and Mathiyalagan Kalidass*
International Journal of Control, Automation, and Systems, vol. 20, no. 10, pp.3241-3251, 2022

Abstract : Robust passivity analysis for stochastic genetic regulatory networks (GRNs) with time-varying delays and Levy noise is addressed in this paper. The main objective is to estimate the true concentrations of mRNA and proteins using the available measured outputs. To analyze the passivity performance for stochastic GRNs a new set of delay-dependent conditions are established with the help of Lyapunov-Krasovskii Functional (LKF), some integral inequalities and free-weighting matrix approach. Further, the results are also extended to analyze the performance of passivity in the presence of uncertainties. The sufficient conditions are expressed as linear matrix inequalities (LMIs), which can be easily solved by Matlab software. Finally, a numerical example is given to demonstrate the usefulness of the proposed model.

Keyword : "Genetic regulatory networks, Levy noise, parameter uncertainties, passivity, time-varying delay. "

 
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