Model-assisted extended state observer-based computed torque control for trajectory tracking of uncertain robotic manipulator systems

Abstract

Computed torque control is an effective control scheme for trajectory tracking of robotic manipulators. However, computed torque control requires precise dynamic models of robotic manipulators and is severely affected by uncertain dynamics. Thus, a new scheme that combines a computed torque control and a novel model-assisted extended state observer is developed for the robust tracking control of robotic manipulators subject to structured and unstructured uncertainties to overcome the disadvantages of computed torque control and exploit its merits. The model-assisted extended state observer is designed to estimate and compensate these uncertain dynamics as a lumped disturbance online, which further improves the disturbance rejection property of a robotic system. Global uniform ultimate boundedness stability with an exponential convergence of a closed-loop system is verified through Lyapunov method. Simulations are performed on a two degree-of-freedom manipulator to verify the effectiveness and superiority of the proposed controller.