Dual-Loop Iterative Learning Control of Robot Manipulator for Human-Robot cooperation

摘要

Abstract This paper proposed a dual-loop iterative learning control strategy for robot manipulator in the situation of repetitive human-robot interaction. By utilizing the contact force between the human and the manipulator, a force-based loop is first conducted to produce the unknown desired trajectory of the manipulator. According to Lyapunov’s method and using the back-stepping technique, an adaptive iterative learning controller is presented to fulfill the trajectory tracking task of the robot manipulator, in spite of the model uncertainties and the unknown disturbances. The proposed control scheme is verified by numerical simulation on a robot manipulator with two degrees-of-freedom.