<title>Robotic hybrid position/force control using artificial neural network</title>

Abstract

A hybrid position/force controller is designed for the joint 2 and the joint 3 of the PUMA 560 robot. The hybrid controller includes a multilayered neural network, which can identify the dynamics of the contacted environment and can optimize the parameters of the PID controller. The experimental results show that after having been trained, the robot has both stable response to the training patterns and strong adaptive ability to the situation between the patterns.