Authors: Haiyong Chen, De Xu, Ping Yang, Hong Wang
Addresses: Department of Automation, Hebei University of Technology, Tianjin, 300130 China. ' Institute of Automation, CAS, Beijing, 100190 China. ' Institute of Automation, CAS, Beijing, 100190 China. ' Control System Centre, Manchester University, Manchester, M60 1QD UK
Abstract: A new scheme to minimise the closed loop randomness for a kind of intelligent welding robot system is presented. It is assumed that the system is subjected from bounded random disturbances. The parameters of controller have been optimised according to a minimum entropy index function by using minimum entropy control method based on an iterative learning frame. As the entropy is the measure of randomness for random variable, the control method advantages to reduce the uncertainty of the closed loop system, which help to obtain a better performance. The iterative learning frame about minimum entropy control has been proposed and is used to optimal the controller parameters. In addition, the convergence of the control algorithm has been analysed. Finally, the effectiveness and feasibility of the proposed control schemes are verified by using an experimental robot.
Keywords: intelligent welding; welding robots; intelligent robots; minimum entropy control; iterative learning control; ILC; robot control.
International Journal of Advanced Mechatronic Systems, 2010 Vol.2 No.1/2, pp.19 - 27
Published online: 10 Jan 2010 *Full-text access for editors Access for subscribers Purchase this article Comment on this article