Nonfragile Finite-Time Stabilization for Discrete Mean-Field Stochastic Systems

In this article, the problem of nonfragile finite-time stabilization for linear discrete mean-field stochastic systems is studied. The uncertain characteristics in control parameters are assumed to be random satisfying the Bernoulli distribution. A new approach called the “state-transition matrix me...

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Bibliographic Details
Published inIEEE transactions on automatic control Vol. 68; no. 10; pp. 6423 - 6430
Main Authors Zhang, Tianliang, Deng, Feiqi, Shi, Peng
Format Journal Article
LanguageEnglish
Published New York The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.10.2023
Subjects
Control theory
Matrix methods
Stabilization
Stochastic systems
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Summary:In this article, the problem of nonfragile finite-time stabilization for linear discrete mean-field stochastic systems is studied. The uncertain characteristics in control parameters are assumed to be random satisfying the Bernoulli distribution. A new approach called the “state-transition matrix method” is introduced and some necessary and sufficient conditions are derived to solve the underlying stabilization problem. The Lyapunov theorem based on the state-transition matrix also makes a contribution to the discrete finite-time control theory. One practical example is provided to validate the effectiveness of the newly proposed control strategy.
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content type line 14
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2023.3238849