신경회로망을 이용한 직류전동기의 센서리스 속도제어

Abstract

DC motor requires a rotor speed sensor for accurate speed control. The speed sensors such as resolvers and encoders are used as speed detectors, but they increase cost and size of the motor and restrict the industrial drive applications. So in these days, many papers have reported on the sensorless operation of DC motor[3]-[5]. This paper presents a new sensorless strategy using neural networks[6]-[8]. Neural network structure has three layers which are input layer, hidden layer and output layer. The optimal neural network structure was tracked down by trial and error, and it was found that 4-16-1 neural network has given suitable results for the instantaneous rotor speed. Also, learning method is very important in neural network. Supervised learning methods[8] are typically used to train the neural network for learning the input/output pattern presented. The back-propagation technique adjusts the neural network weights during training. The rotor speed is gained by weights and four inputs to the neural network. The experimental results were found satisfactory in both the independency on machine parameters and the insensitivity to the load condition.