Adaptive control of robot manipulators - A review

Abstract

Adaptive control has been recognized as an effective approach for mechanical robot manipulator controller design due to the presence of nonlinearties and uncertainties in robot dynamic models. Numerous results addressing different aspects of the control problem have been reported in the literature in recent years. The purpose of this paper is to present an indepth review of these existing developments whereby the robot adaptive control problems and solutions are systematically studied. The essential overall objective is to unify the various design ideas under a common frame work. Within this frame work, the various design techniques are catagorized into three groups; (i) model-reference adaptive control, (ii) Self tuning adaptive control, and (iii) Linear perturbation adaptive control. The design conditions and solutions of each technique are discussed, and the relationships between these techniques are examined. Finally some remarks on the effectiveness and implementation of adaptive controllers are presented.