Global sampled-data output feedback stabilization for a class of stochastic nonlinear systems with time-varying delay

被引：18
|
作者：
He, Wenmin [1 ]
Guo, Jian [1 ]
Xiang, Zhengrong [1 ]
机构：
[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Jiangsu, Peoples R China
来源：
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2019年 / 356卷 / 01期
基金：
中国国家自然科学基金;
关键词：
ADAPTIVE NEURAL-CONTROL; UNKNOWN DEAD-ZONES; NETWORKS; TRACKING; SUBJECT; DESIGN;
D O I：
10.1016/j.jfranklin.2018.11.010
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper studies the global sampled-data output feedback stabilization problem for a class of stochastic nonlinear systems. The considered system is in non-strict feedback form with unknown time-varying delay. A state observer is introduced to estimate the unmeasured states. With the help of the backstepping method, a linear sampled-data output feedback controller is constructed. By choosing an appropriate Lyapunov-Krasoviskii functional and an allowable sampling period, it is shown that the stochastic system can be globally asymptotically stabilized in the mean square sense under the developed control scheme. Finally, two examples are presented to verify the effectiveness of the designed control scheme. (C) 2018 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：292 / 308
页数：17
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