The Design of BP Neural Network Modeling for Switched Reluctance Motor

DOI

10.2991/eee-19.2019.28How to use a DOI?

Keywords

Switched reluctance motor, DSP TMS320LF2407, BP network, Flux linkage characteristic

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.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Dong-kai Qiao
AU  - Mei-qing Cai
AU  - Guo-le Li
PY  - 2019/07
DA  - 2019/07
TI  - The Design of BP Neural Network Modeling for Switched Reluctance Motor
BT  - Proceedings of the 2nd International Conference on Electrical and Electronic Engineering (EEE 2019)
PB  - Atlantis Press
SP  - 164
EP  - 168
SN  - 2352-5401
UR  - https://doi.org/10.2991/eee-19.2019.28
DO  - 10.2991/eee-19.2019.28
ID  - Qiao2019/07
ER  -