Adaptive Output-Feedback Control for Stochastic Nonlinear Systems Using Neural Networks

被引：0
|
作者：
Min Hui-Fang [1 ]
Duan Na [1 ]
机构：
[1] Jiangsu Normal Univ, Sch Elect Engn & Automat, Xuzhou 221116, Peoples R China
来源：
2014 33RD CHINESE CONTROL CONFERENCE (CCC) | 2014年
关键词：
Stochastic Nonlinear Systems; Output-Feedback Control; Neural Networks; Unknown Control Directions; Tuning Function; STABILIZATION; TRACKING;
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：
This paper considers the output-feedback control problem for a class of stochastic nonlinear systems with unknown control directions and perturbations. By using radial basis function neural network (RBF NN) approximation approach, the tuning function method and backstepping technique, an adaptive output-feedback controller is successfully constructed to guarantee the closed-loop system to be mean square semi-globally uniformly ultimately bounded (M-SGUUB). A simulation example demonstrates the effectiveness of the proposed scheme.
引用
收藏
页码：5288 / 5293
页数：6
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