On Analysis and Implementation of Iterative Learning Control

Abstract

Many of the control systems used in factory production today are programmed to perform the same task repeatedly. In particular this is the case for industrial robots where the same motion is performed every time the same program is executed. An interesting observation, for the industrial robot, is that the error in the different iterations of the same exercise is highly repetitive. In the thesis Iterative Learning Control is applied to an industrial robot control system from ABB. Using Iterative Learning Control the tracking error on the motor side has been reduced without changing the internal structure or any parameters in the robot controller. The results from the experiments show that Iterative Learning Control can be used to successfully reduce the tracking error in an industrial robot control system. The implementation of the functions needed in the robot controller is described. By using a combination of already present functions in the system and software development the Iterat...