Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
762476 | Energy Conversion and Management | 2006 | 9 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Energy
Energy (General)
Authors
Ferhat Daldaban, Nurettin Ustkoyuncu, Kerim Guney,