Minimum Entropy Control of a Kind of Intelligent Welding Robot
This paper presents a new scheme to minimize the closed loop randomness for a kind of macro-micro welding robot system. The system is assumed to be subjected to any bound random noises. Using recently developed minimum entropy control based on iterative learning, the parameters of controller have been optimized according to minimum entropy index function. As the entropy is the measure of randomness for a desired random variable, this control method can reduce the uncertainty of the closed loop system. The iterative learning frame about minimum control has been proposed. In addition, the convergence condition of control algorithm has been analyzed. Finally, an experimental macro-micro robot is used to illustrate the effectiveness and feasibility of the proposed control schemes.
macro-micro robot minimum entropy iterative learning control
Haiyong Chen De Xu Ping Yang Hong Wang
Department of Automation Hebei University of Technology Tianjin, China Institute of Automation Chinese Academy of Sciences Beijing, China Control System Centre Manchester University Manchester,UK
国际会议
2008 Sino-European Workshop on Intelligent Robots and Systems(SEIROS08)(第一届中欧智能系统及机器人国际学术研讨会)
重庆
英文
1-6
2008-12-11（万方平台首次上网日期，不代表论文的发表时间）