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Control of Switched Reluctance Motors based on Improved BP Neural Networks

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成果类型:
期刊论文
作者:
Xiao Jin-Feng;Xiao Qi-Ming
通讯作者:
Jin-Feng, Xiao(jinfengxiaosheng@163.com)
作者机构:
[Xiao Jin-Feng] School of Electrical Engineering, University of South China, Hengyang
Hunan
421001, China
[Xiao Qi-Ming] Foxconn Wireless Business Group, Hengyang
[Xiao Jin-Feng; Xiao Qi-Ming] Hunan
通讯机构:
School of Electrical Engineering, University of South China, Hengyang, Hunan, China
语种:
英文
关键词:
Switched reluctance motor;BP neural network;artificial fish swarm;particle swarm optimization;BP algorithm;global optical value.
期刊:
Recent Advances in Electrical & Electronic Engineering
ISSN:
2352-0965
年:
2018
卷:
11
期:
2
页码:
97-102
机构署名:
本校为第一且通讯机构
院系归属:
电气工程学院
摘要:
Background: Switched reluctance motors have a strong nonlinear performance due to their structure and operation mode. The performance and control strategy of this kind of motor are obviously different from those traditional strategies. As a result, the accurate model and high performance control of the switched reluctance motor prove to be very important and has obtained wide researches. Method: A kind of switched reluctance motor based on PID neural network control strategy is proposed, which combines artificial fish swarm and particle swarm o...

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