Hybrid PD-PID with Iterative Learning Control for Two-Link Flexible Manipulator

Abstract

An iterative learning scheme consisting of feedforward learning controllers and hybrid feedback PD-PID controllers are developed for two-link flexible manipulator. The PD controllers ensure the hubs track desired trajectory through hub angle and joint velocity feedback while the PID controllers suppress link vibration through end-points acceleration feedback. The iterative learning control in the feedforward paths are used to improve overall performance of the robot (e.g. input tracking and vibration suppression) by predicting the desired controlled torque. The proposed learning scheme is simple, efficient and easy to implement even with existing controller. Numerical simulation was carried out in Matlab/Simulink environment to show the effectiveness of the proposed control schemes. The reduction in tracking error and system vibration shows that the predicted actuator torques converge to the desired torques as iteration number increases. The performance of the proposed controller in terms of input tracking and vibration suppression is presented and compared with hybrid PD-PID controller. To demonstrate the robustness of the proposed control schemes effect of payload variation is also studied.