The Design of BP Neural Network Modeling for Switched Reluctance Motor
Dong-kai Qiao, Mei-qing Cai, Guo-le Li
Available Online July 2019.
- https://doi.org/10.2991/eee-19.2019.28How to use a DOI?
- Switched reluctance motor, DSP TMS320LF2407, BP network, Flux linkage characteristic
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/eee-19.2019.28 ID - Qiao2019/07 ER -