Adaptive control of robot manipulators using fuzzy logic systems under actuator constraints

Abstract

In this paper, a stable fuzzy adaptive controller for trajectory tracking is developed for robot manipulators without velocity measurements, taking into account the actuator constraints. The controller is based on structural knowledge of the dynamics of the robot and measurements of link positions only. The gravity torque including system uncertainty like payload variation, etc., is estimated by a fuzzy logic system (FLS). The adaptive controller represents an amalgamation of a filtering technique to eliminate velocity measurements and the theory of function approximation using FLS to estimate the gravity torque. The proposed controller ensures the local asymptotic stability and the convergence of the position error to zero. The proposed controller is robust not only to structured uncertainty such as payload parameter variation, but also to unstructured one such as disturbances. The validity of the control scheme is shown by simulations on a two-link robot manipulator.