Control of industrial robot using neural network compensator

Vesna Ranković, Ilija Nikolić

In the paper is considered synthesis of the controller with tachometric feedback with feed forward compensation of disturbance torque, velocity and acceleration errors. It is difficult to obtain the desired control performance when the control algorithm is only based on the robot dynamic model. We use the neural network to generate auxiliary joint control torque to compensate these uncertainties. The two-layer neural network is used as the compensator. The main task of control system here is to track the required trajectory. Simulations are done in MATLAB for $R_zR_yR_y$ robot minimal configuration.