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

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.

关键词： Stochastic Nonlinear Systems Output-Feedback Control Neural Networks Unknown Control Directions Tuning Function

作者: Min Hui-Fang Duan Na

作者单位: School of Electrical Engineering & Automation,Jiangsu Normal University,Xuzhou 221116,P.R.China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 5288-5293

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）