Adaptive robust fuzzy control for dual arm robot with unknown input deadzone nonlinearity

Abstract

The control problem of the dual arm robot rigidly grasping an object with unknown nonsymmetric deadzone input is investigated in this paper. Due to the factor that the deadzone nonlinearity is widespread in the actuators, a smooth inverse adaptive deadzone is incorporated to minimize the effect of the deadzone nonlinearity in the dual arm robot system to guarantee a high accuracy tracking. Since these type of robots are usually applied in complex environments, a multi-input multi-output fuzzy logic unit is adopted to approximate the manipulator’s dynamics to achieve a accuracy tracking performances. Moreover, a decentralized robust fuzzy adaptive control scheme is constructed to make the motion and internal forces track a reference trajectories in the presence of parameters uncertainty and external disturbance. By using the Lyapunov method, the stability of the signals in the closed-loop system is proved. Simulation result demonstrates that the proposed controller is effective to the dual arm robot system with deadzone nonlinearity.