Phase inductance estimation for switched reluctance motor using adaptive neuro-fuzzy inference system

被引：38
|
作者：
Daldaban, F [1 ]
Ustkoyuncu, N [1 ]
Guney, K [1 ]
机构：
[1] Erciyes Univ, Fac Engn, Dept Elect Engn, TR-38039 Kayseri, Turkey
来源：
ENERGY CONVERSION AND MANAGEMENT | 2006年 / 47卷 / 05期
关键词：
switched reluctance motor; ANFIS; neuro-fuzzy inference system; inductance;
D O I：
10.1016/j.enconman.2005.05.020
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
A new method based on an adaptive neuro-fuzzy inference system (ANFIS) for estimating the phase inductance of switched reluctance motors (SRMs) is presented. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the ANFIS. The rotor position and the phase current of the 6/4 pole SRM are used to predict the phase inductance. The phase inductance results predicted by the ANFIS are in excellent agreement with the results of the finite element method. (c) 2005 Elsevier Ltd. All rights reserved.
引用
收藏
页码：485 / 493
页数：9
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