Novel Statistic Information Control Framework for Non-Gaussian Stochastic Systems With Dead-Zone Input

摘要：

In this paper, a novel statistic information control framework is studied for non-Gaussian stochastic systems with dead-zone input. Different from both the traditional stochastic optimization objective for Gaussian systems and the PDF tracking objective for Non-Gaussian systems, the driven information and the controlled objective for control problem is the statistic information set (SIS) of the system output. Only one step neural network identification and control is considered to solved the statistic information tracking control problem. Furthermore, the stability analysis for both the identification and tracking errors is developed via the use of Lyapunov stability criterion. Computer simulations are given to demonstrate the efficiency of the proposed approach.

关键词： non-Gaussian system statistic information set dead-zone input statistic information control

作者: YI Yang LIU Yunlong CAO Songyin

作者单位: College of Information Engineering, Yangzhou University, Yangzhou 225127, China Institute of Automat School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 1000 College of Information Engineering, Yangzhou University, Yangzhou 225127, China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 1640-1644

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）