Neural fuzzy control to minimise torque ripple of SRM

被引：1
|
作者：
Liu, Jian [1 ,2 ]
Qiao, Feng [1 ]
Liu, Meiju [1 ]
Wu, Chengdong [2 ]
机构：
[1] Shenyang Jianzhu Univ, Fac Informat & Control Engn, 9 Hunnan East Rd, Shenyang 110168, Liaoning, Peoples R China
[2] Northeastern Univ, Fac Informat Sci & Engn, Shenyang 110004, Liaoning, Peoples R China
来源：
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL | 2010年 / 10卷 / 1-2期
关键词：
neural networks; fuzzy control; switched reluctant motor; torque ripple reduction;
D O I：
10.1504/IJMIC.2010.033856
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The switched reluctance motor (SRM) exhibits high non-linear characteristics, so it is difficult to employ conventional control algorithms to achieve the desired dynamic performances for non-linear SRMs. It is proposed, in this paper, a new kind of neural fuzzy controller to tackle the problem of torque ripple reduction in switched reluctance motor drive, which does not require the precise mathematical model of the system and offers an obvious advantage over traditional PID control system. The simulation results show that the neural fuzzy control strategy possesses superior performance in reducing low frequency torque ripple and torque dip, and demonstrate the effectiveness and feasibility of the proposed scheme.
引用
收藏
页码：132 / 137
页数：6
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