Adaptive quantized control of switched stochastic nonlinear systems

被引：31
|
作者：
Wang, Fang [1 ,2 ]
Chen, Bing [1 ]
Lin, Chong [1 ]
Li, Gang [2 ]
Sun, Yumei [1 ]
机构：
[1] Qingdao Univ, Inst Complex Sci, Qingdao 266071, Peoples R China
[2] Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao, Shandong, Peoples R China
来源：
NEUROCOMPUTING | 2016年 / 207卷
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Adaptive fuzzy control; Backstepping technique; Switched stochastic nonlinear systems; Quantized input; TRACKING CONTROL; LINEAR-SYSTEMS; FEEDBACK STABILIZATION; STABILITY; STABILIZABILITY; DESIGN; TIMES;
D O I：
10.1016/j.neucom.2016.05.024
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper is concerned with a tracking control issue for a class of switched stochastic systems with quantized input. To overcome the difficulty caused by the switching and quantization, a nonlinear decomposition strategy for quantizer is firstly proposed, then by using the common Lyapunov function method, a systematic adaptive control scheme is presented. It is proved that, under the proposed control scheme, the good control performance is obtained although influenced by the effect of switching and quantization. Furthermore, the validity of the proposed control scheme is verified by the simulation results. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码：450 / 456
页数：7
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