DESIGN ADAPTIVE ROBUST FUZZY CONTROLLER FOR ROBOT MANIPULATORS

Abstract

This paper proposes an adaptive robust Fuzzy controller based on Backstepping scheme to solve with the model unknown and parameter disturbances for robot manipulator. In this research, the robust adaptive fuzzy system is combined with Backstepping design method to remove the matching condition requirement and to provide boundedness of tracking errors, even under dominant model uncertainties. Unlike previous robust adaptive fuzzy controllers of nonlinear systems, the robustness term of proposed control scheme is selected as an auxiliary controller in the control system to deal with the effects of model uncertainties and parameter adaptation errors. The adaptive turning laws of network parameters are derived using the Lyapunov stability theorem, therefore, the global stability and robustness of the entire control system are guaranteed, and the tracking errors converge to the required precision, and position is proved.  Finally, the effectiveness of the proposed robust adaptive control methodology is demonstrated by comparative simulation results with the adaptive Backstepping control (BPC) and the adaptive Fuzzy control (AFC), which have done on three-joint robot manipulator.