Journal
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
Volume 19, Issue 3, Pages 1651-1660Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TCBB.2020.3040979
Keywords
Switched genetic regulatory networks; finite-time H-infinity state estimation; persistent dwell-time switching rule; randomly occurring uncertainties
Categories
Funding
- National Natural Science Foundation of China [61703004, 61873002]
- Natural Science Foundation of Anhui Province [1808085QA18]
- National Research Foundation of Korea (NRF) - Korea government (MSIT) [2020R1A2B5B02002002]
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This article addresses the problem of finite-time H-infinity state estimation for switched genetic regulatory networks with randomly occurring uncertainties. It proposes a versatile switching rule and utilizes random variables obeying the Bernoulli distribution to represent the uncertainties. The article aims to design an estimator that ensures the boundedness of estimation error system and satisfies the H-infinity performance.
This article is concerned with the problem of finite-time H-infinity 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 article is to design an estimator to ensure that the estimation error system is stochastically finite-time bounded and satisfies the H-infinity 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.
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