Adaptive Fuzzy Control for Stochastic Nonlinear Systems via Sliding Mode Method

被引：6
|
作者：
Wang, Zengyun [1 ]
Huang, Lihong [2 ,3 ]
Yang, Xuxin [1 ]
Xin, Aitong [4 ]
机构：
[1] Hunan First Normal Univ, Dept Math, Changsha 410205, Hunan, Peoples R China
[2] Hunan Univ, Coll Math & Economtr, Changsha 410082, Hunan, Peoples R China
[3] Hunan Womens Univ, Changsha 410003, Hunan, Peoples R China
[4] Hunan First Normal Univ, Dept Informat Sci & Engn, Changsha 410205, Hunan, Peoples R China
来源：
CIRCUITS SYSTEMS AND SIGNAL PROCESSING | 2013年 / 32卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Adaptive fuzzy controller; Nonlinear; Stochastic system; Sliding mode; Wiener process; CHAOS SYNCHRONIZATION;
D O I：
10.1007/s00034-013-9602-7
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, an adaptive fuzzy controller is designed for a nonlinear stochastic system to track the given reference via the sliding mode method. The nonlinear stochastic system is modeled by a deterministic nonlinear system with white noise obtained from the derivative of a Wiener process, which eventually generates an It differential equation. Compared with existing results, the main advantage is that information of the nonlinear functions is not required. Under the designed controller with the proposed update laws, the tracking error trajectories converge to an arbitrary small region around zero in the mean square norm. Simulations to show the efficiency of the proposed controller are provided.
引用
收藏
页码：2839 / 2850
页数：12
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