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

被引：0

作者：

Miao, Xiufeng ^{[1
]}

Xu, Yaoqun ^{[2
]}

Yao, Fengge ^{[3
]}

机构：

[1] Harbin Univ Commerce, Northeast Asia Serv Outsourcing Res Ctr, Harbin 150028, Peoples R China

[2] Harbin Univ Commerce, Comp & Informat Engn Coll, Harbin 150028, Peoples R China

[3] Harbin Univ Commerce, Sch Finance, Harbin 150028, Peoples R China

来源：

MATHEMATICS | 2023年 / 11卷 / 04期

关键词：

parameter uncertainty; discrete-time; ultimately exponentially bounded; stochastic systems; STABILITY; THEOREMS;

D O I：

10.3390/math11040973

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

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.

引用

页数：7