Robust Adaptive Control for Robot Manipulators Using Regressor-Based Form

In this paper, a robust adaptive control scheme is proposed for robot manipulators. The structure of controller is based on the regressor-based form of the robot model. The presented control scheme does not require a priori any knowledge for uncertainty bounds. The global stability of the closed-loop system is guaranteed by using the Lyapunov stability approach. Furthermore, in the presence of the measurement noise, it is shown that the tracking errors are uniformly ultimately bounded. Consequently, it is found that the proposed control scheme guarantees global boundedness of the tracking errors under parameter variations, disturbances and measurement noises. Simulation results are presented to show the feasibility and the effectiveness of the proposed control scheme.