Ultimately Exponentially Bounded Estimates for a Class of Nonlinear Discrete−Time Stochastic Systems

In this paper, the ultimately exponentially bounded estimate problem of nonlinear stochastic discrete−time systems under generalized Lipschitz conditions is considered. A new sufficient condition making the estimation error system uniformly exponentially bounded in the mean square sense is given. Th...

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Bibliographic Details
Published inMathematics (Basel) Vol. 11; no. 4; p. 973
Main Authors Miao, Xiufeng, Xu, Yaoqun, Yao, Fengge
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.02.2023
Subjects
Analysis
Boundary value problems
Conflicts of interest
Control theory
Discrete-time systems
discrete−time
Estimation theory
Inequality
Mathematical research
Methods
Nonlinear functional analysis
Nonlinear theories
parameter uncertainty
Random variables
Stochastic processes
Stochastic systems
ultimately exponentially bounded
China
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Summary:In this paper, the ultimately exponentially bounded estimate problem of nonlinear stochastic discrete−time systems under generalized Lipschitz conditions is considered. A new sufficient condition making the estimation error system uniformly exponentially bounded in the mean square sense is given. The gain matrix can be obtained by solving matrix inequality. In the last section, numerical examples are provided verify the effectiveness of the conclusions.
ISSN:2227-7390
2227-7390
DOI:10.3390/math11040973