Symbolic computation-based synthesis of neural network dynamics and controller for robots

An application of neural network-based techniques to model and control a robot arm equipped with revolute joints is presented. The use of symbolic means for neural models synthesis is shown. The steps of the calibration process and the way of using the calibrated model in a typical computed torque controller are described. The performance of the controller is illustrated with an example.