Neural network compensation control of robot computed torque uncertainties
机器人计算力矩不确定性的神经网络补偿控制*

This paper proposed a novel control scheme, whick was based on the combination of computed torque control as a feed-forward structure and a neural network as a compensation structure, to improve the computed torque control uncertainties of a pol.ishing robot. The resulting control scheme had a simple structure with enhanced robustness. Since the neuro-compensator had good adaptability, accurate knowledge of both the robot dynamic parameters and structure were not required in advance. Simulation studies on robot trajectory tracking verify the robustness and anti-disturbance capacity of the proposed control method.