Adaptive fuzzy sliding mode controller for end-effector tracking of redundant manipulators

This paper presents an adaptive fuzzy logic sliding model controller (AFSMC) for the redundant robotic manipulator system with uncertain environment. The AFSMC is characterized by the fact of the strong robustness and better accurate position-tracking control to deal with the uncertain and external disturbances. Firstly, a robotic dynamic model including dynamic uncertain model and the external disturbance has been established. Secondly, the sliding model controller based on the switching gain calculated by adaptive fuzzy algorithm has been designed to improve tracking performance in task space. Moreover Lyapunov theory has been applied to demonstrate the stability of the proposed closed-loop robotic system. Finally, the effectiveness of the proposed control approach and theoretical discussion are illustrated through comparative simulations on a seven-link robot manipulator and tested on the humanoid robot platform.