Decentralized Robust Fuzzy Adaptive Control of Humanoid Robot Manipulation With Unknown Actuator Backlash

Abstract

Due to the fact that backlash nonlinearity is widespread in actuators, it is impossible to ignore its existence and achieve excellent and desirable mechanical system performance. In this paper, the problem of the humanoid robot grasping a common object with unknown actuator backlash is investigated. To tackle the nonsmooth backlash nonlinearity, a smooth adaptive backlash inverse is incorporated to compensate the line-segment effect. Moreover, a decentralized robust fuzzy adaptive control is constructed and developed to guarantee the object's motion and internal forces converge to the predefined values. The stabilities of the signals in the closed-loop system are proven by utilizing the Lyapunov method. In the end, experiments and simulations involving humanoid robot manipulation are conducted to validate the effectiveness of the proposed algorithms.