Ultimately Exponentially Bounded Estimates for a Class of Nonlinear Discrete−Time Stochastic Systems
Xiufeng Miao (),
Yaoqun Xu and
Fengge Yao
Additional contact information
Xiufeng Miao: Northeast Asia Service Outsourcing Research Center, Harbin University of Commerce, Harbin 150028, China
Yaoqun Xu: Computer and Information Engineering College, Harbin University of Commerce, Harbin 150028, China
Fengge Yao: School of Finance, Harbin University of Commerce, Harbin 150028, China
Mathematics, 2023, vol. 11, issue 4, 1-7
Abstract:
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.
Keywords: parameter uncertainty; discrete?time; ultimately exponentially bounded; stochastic systems (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2227-7390/11/4/973/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/4/973/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:11:y:2023:i:4:p:973-:d:1068042
Access Statistics for this article
Mathematics is currently edited by Ms. Emma He
More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().