Sampled-data stabilization for a class of stochastic nonlinear systems based on the approximate discrete-time models

被引：0

作者：

Fu, Xinxin ^{[1
]}

Kang, Yu ^{[1
,2
,3
]}

Li, Pengfei ^{[1
]}

机构：

[1] Univ Sci & Technol China, Dept Automat, Hefei, Peoples R China

[2] Univ Sci & Technol China, Inst Adv Technol, State Key Lab Fire Sci, Hefei, Peoples R China

[3] Chinese Acad Sci, Key Lab Technol Geospatial Informat Proc & Applic, Beijing, Peoples R China

来源：

2016 AUSTRALIAN CONTROL CONFERENCE (AUCC) | 2016年

基金：

中国国家自然科学基金;

关键词：

RECEDING HORIZON CONTROL; EULER-MARUYAMA METHOD; DIFFERENTIAL-EQUATIONS; CONVERGENCE-RATES; STABILITY;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we mainly focus on the sampled-data exponential stabilization in mean square for a class of stochastic nonlinear systems based on their Euler-Maruyama model. The relation of the pth moment exponential stability between the sampled-data systems and its exact discrete-time models is discussed; then we present Lyapunov theorem for pth moment exponential stability of discrete-time stochastic nonlinear systems and its converse theorem; the conditions for exponential stabilization in mean square for such sampled-data stochastic nonlinear systems based on their Euler-Maruyama approximation are given. The results provide a simpler and more convenient controller design method for such sampled-data systems, and the effectiveness of the approach is demonstrated in simulation example.

引用

页码：258 / 263

页数：6

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