Bilateral Control with Disturbance Observer and Adaptive Neural Network Compensation

The bilateral control system realizes the position tracking and force transmission between a master robot and a slave one. However, it is a problem to improve the performance of a bilateral control system. In order to further compensate the equivalent disturbance and improve the synchronization performance between the master and slave robots, a four-channel bilateral control system with adaptive neural network is proposed. The proposal is to add a radial basis function (RBF) neural network (NN) to the position control channel to further compensate the deviation between the controlled robots and the models. The stability of the controller is analyzed. Simulation verifies the effectiveness of the proposal.