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
收藏
页码：258 / 263
页数：6
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