An adaptive fuzzy approach for robot manipulator tracking

Abstract

An adaptive fuzzy logic controller is proposed for trajectory tracking control of robot manipulators. The approach uses quantitative control schemes to ensure global stability and qualitative control schemes to approximate any nonlinear functions caused by disturbances, system uncertainties and interconnections. With the PD control as a preliminary component in maintaining the local stability, we add nonlinear feedback to ensure global stability of the entire system. An adaptive fuzzy logic controller is incorporated into the robot arm control system as a function approximator to compensate the interconnections effect, unmodeled dynamics, friction, gravity force and uncertainties. The stability criteria of the proposed controller is developed using the Lyapunov synthesis approach. Computer simulations show that the proposed adaptive fuzzy controller outperforms traditional control approaches.