Application of neural network controller in the seam tracking of arc-welding robot

A neural network(NN) controller which improves the accuracy of seam tracking of an arc-welding robot is presented in this paper. The improvement of tracking accuracy can be achieved by applying the NN controller for compensating for model uncertainties of robot manipulator. Unlike the traditional NN compensation of model uncertainties which was carried through by modifying the joint/force of the robot, the proposed NN compensation is used to modify the reference Cartesian seam trajectory, which is easily applied in practice. The required internal signal level of proposed NN for the seam modification is much smaller. Simulations and experiments have been performed on an actual arc-welding robot manipulator to test the effectiveness of NN control scheme. It has been found that NN can generate better tracking performance than the traditional computed torque(CT) control method which is based on the manipulator dynamics only. One goal of this paper is to stimulate further discussion of application of NN in the arc-welding robot control.