Improved Tracking Control for Robots Using Neural Networks

Abstract

The tracking control of robots in joint space is studied in this paper. A new control algorithm is proposed based on the well known computed torque method and a feedforward compensating controller. The function of the feedforward controller, which is realized using an RBF neural network, is to provide high tracking accuracy of robot path following performance. It is demonstrated through simulations that the proposed scheme could achieve much better tracking performance.