A scheme on the force and motion control of manipulator robots based on a neural network

In this paper, a computed-torque control scheme based on the BP algorithm is proposed. The control scheme is an efficient combination of a computed-torque control and a neural network as a compensation structure, which enhances the adaptability of the controller. Based on the Lyapunov stability theorem, it is shown that the new scheme can guarantee tracking performance of the robotic manipulator. Furthermore, the scheme showed a good performance when it was applied to the force control. The results of the simulations and experiments verified the effectiveness of the proposed scheme.