Chattering-Suppressed Sliding Mode Control for Flexible-Joint Robot Manipulators

In this paper, sliding mode tracking control and its chattering suppression method are investigated for flexible-joint robot manipulators with only state measurements of joint actuators. First, within the framework singular perturbation theory, objective system is decoupled into two typical aims a slow subsystem fast subsystem. Then, considering lumped uncertainties (including dynamics external disturbances), composite chattering-suppressed controller proposed, where smooth-saturation-function-contained reaching law adjustable saturation factor designed to alleviate inherent phenomenon, radial basis function neural network (RBFNN)-based soft computing strategy applied avoid high switching gain that leads amplification. Simultaneously, an efficient extended Kalman filter (EKF) respect new variable presented enable closed-loop neither position nor velocity links. addition, overall analysis on asymptotic stability whole given. Finally, numerical examples verify superiority dynamic performance proposed approach, which well qualified suppress can effectively eliminate undesirable effects smaller reduced by 80% in comparison without RBFNN. The computational efficiency EKF increased about 26%.