Adaptive controllers that employ saturated error update laws for robot trajectory tracking

Abstract

This paper presents two new adaptive schemes that employ adaptive update laws based on saturated error for the motion control of robot manipulators. The proposed controllers are very general and computationally efficient since they do not require knowledge of either the mathematical model or the parameter values of the manipulator dynamics, and are implemented without calculation of the robot inverse dynamics or inverse kinematic transformations. It is shown that the control strategies are globally uniformly bounded in the presence of bounded disturbances, and that in the absence of disturbances the ultimate bound on the size of the tracking errors can be made arbitrarily small. Computer simulation results are given for a PUMA 560 manipulator, and demonstrate that accurate and robust trajectory tracking can be achieved by using the proposed controllers.