Finite-Time H State Estimation for PDT-Switched Genetic Regulatory Networks With Randomly Occurring Uncertainties

Abstract

This paper is concerned with the problem of finitetime H∞ state estimation for switched genetic regulatory networks with randomly occurring uncertainties. The persistent dwell-time switching rule, as a more versatile class of switching rules, is considered in this paper. Besides, several random variables that obey the Bernoulli distribution are used to represent randomly occurring uncertainties. The overriding purpose of this paper is to design an estimator to ensure that the estimation error system is stochastically finite-time bounded and satisfies the H∞ performance. Based on this, sufficient conditions for the explicit form of the estimator gains can be obtained by the Lyapunov method. Finally, a numerical example is given to verify the correctness and feasibility of the proposed method. Index Terms-Switched genetic regulatory networks, finitetime H∞ state estimation, persistent dwell-time switching rule, randomly occurring uncertainties.

Finite‐time secure state estimation for a class of switched systems subject to deception attacks

“…Moreover, the estimation error dynamics of time‐delayed genetic regulatory networks were modeled as a Markovian switched system with two switched signals. Wang et al 38 also studied the issue of finite‐time $$$ {H}_{\infty } $$$ state estimation for switching genetic regulatory networks by considering the randomly occurring uncertainties that have been present as a Bernoulli process. Furthermore, the authors looked into the finite‐time state and the fault estimation problem for descriptor switched systems 39 …”