Adaptive Fuzzy Computed-Torque Control for Robot Manipulator with Uncertain Dynamics

Abstract

To overcome the disadvantages of conventional computed-torque control and fuzzy control, and to exploit their attractive features, this paper proposes two types of adaptive control scheme combining conventional computed-torque control and different fuzzy compensators for the robust tracking control of robotic manipulators with structured and unstructured uncertainties. Fuzzy compensators based on feed-forward and feed-back are developed to compensate these uncertain dynamics. On the basis of Lyapunov stability theory, a tracking error limit is derived for the closed-loop control system and the convergence and stability of the control schemes are proved. Comparisons of their performances with conventional computed-torque controllers under the condition of these uncertainties are carried out. The validity of the two types of adaptive control scheme is shown by numerical simulations of a three-link rotary robot manipulator.