Adaptive tracking control with uncertainties for robots

In this paper, an adaptive Jacobian tracking control of robot manipulators is presented. The proposed controller is based on the inverse robot manipulator dynamics and estimated uncertainty which can compensate for the uncertain parameters and external disturbances. Using the Lyapunov approach, the paper incorporates sliding mode control to enhance the asymptotic stability that shows the tracking errors of end-effector motion converge asymptotically to zero. Simulation results are presented to show the robustness and the performance of the proposed controller applied to a two-degrees of freedom (2DOF) manipulator.