The Design of BP Neural Network Modeling for Switched Reluctance Motor

Abstract

The model parameters of 8/6 poles switched reluctance motor (SRM) were determined through using the measured magnetization curve and the establish BP neural network model, selecting Sigmoid function as the hidden layer activation function and using gradient descent method to train the network. The simulated results show that the motor flux linkage model established has a good convergence rate, higher accuracy and generalization ability. It is significant to improve the reliable running and high precision speed control of SRM motor. BP Neural Network Modeling Based on the sample shown as magnetization curve by measuring[13], we can come up with a model which aims at SRM's BP neural network magnetic linkage model.