Achieving accurate trajectory tracking control of robot manipulators is challenging due to dynamic model errors and uncertain payloads. This paper aims to enhance trajectory tracking performance for robots with n degrees of freedom (DOF).
This study proposes a robust motion control framework that combines uncertainty and disturbance estimator with model-based compensation. The proposed framework ensures precise trajectory tracking in robot manipulators. In addition, uncertainties in the high-DOF robot dynamics are estimated through a simple model-based compensation for system error dynamics. The stability of the closed-loop system of the proposed framework is analyzed and proved.
The results indicate that the proposed framework can significantly reduce tracking errors and increase disturbance resistance. The simulation results of a two-link robotic arm verify the effectiveness of the proposed method. The results of the experiments conducted on a seven-DOF torque-controlled Flexiv4S manipulator demonstrate the superior trajectory tracking performance and robustness of the proposed algorithm.
This study introduces a highly efficient, robust motion control framework for high-DOF robots, which can improve the trajectory tracking performance in the presence of model uncertainties.
