Adaptive Iterative Learning Trajectory Tracking Control of SCARA Robot

Abstract

Taking SCARA robot as the research object, an Adaptive Iterative Learning Control algorithm is used to solve the problems of slow speed, large pose error and poor anti-interference ability of conventional controller in robot trajectory tracking control. The model of robot control system is established by using SIMULINE, and the random disturbance signal input of the system is set. Given the trajectory of linear and curvilinear moving targets, the trajectory tracking control is verified. The experiment results show that, compared with the conventional controller, the Adaptive Iterative Learning Control method could control the end trajectory of the robot more accurately, the tracking speed is faster, the tracking attitude is more accurate, and it has good feasibility and portability.