Application of Neural Network-Based Servo Controller to Position, Force and Stabbing Control by Robotic Manipulator.

Abstract

In this paper, a new concept of a "Neural Servo Controller" is presented to show the applicability of the neural network to position and force, control of robotic manipulators. The proposed Neural Servo Controller is based on the self-organization capability of the neural network, which here consisfs of two hidden layers, and input/output layers. The controller can adjust the neural network output to the robot in the forward manner to cooperate with the feedback loop, depending on different characteristics of handling objects. In particular, the neural network can recognize the force-control modes. The proposed method can adapt the network of stabbing control to one with applications of position and force control. Simulations and experiments are carried out in the case of one-dimensional robotic manipulators. The results show the applicability and the adaptability of the proposed Neural Servo Controller to position/force control of manipulators.