Intelligent Control of Alternative Current Permanent Magnet Servo-motor Using Neural Network

摘要

A momentum back-propagation neural network is applied to control of alternative current permanent magnet servo-motors operating in a high performance drives environment to inhibit the network from converging at the local minimum point. The emerging back-propagation neural networks have the capability to learn arbitrary non-linearity and show great potential for intelligent control applications. A scheme for combing momentum back-propagation neural networks with traditional PID control techniques is proposed. The control action emulated by aids of MATLAB show that the new self-turning scheme can deal with a large unknown non-linearity.