Speed Sensorless Vector Controlled Induction Machine in Flux Weakening Region

Author

Moulahoum, Samir ; Touhami, Omar ; Rezzoug, Abderrezak ; Baghli, Lotfi

Author_Institution

Departement de Genie Electrique, ENP 10, Alger

fYear

2006

fDate

6-10 Nov. 2006

Firstpage

1206

Lastpage

1211

Abstract

The aim of this paper is to examine iron losses and magnetic saturation effect in sensorless vector control of induction machines. First of all, an approach to induction machine modelling and vector control scheme, which account for both iron loss and saturation, is presented. Then, a model reference adaptive system (MRAS) speed estimator is developed. To improve the performance of the rotor speed estimation, particularly, in the flux weakening region, an artificial neural network (ANN) is used. The ANN flux estimator is substituted into the MRAS speed estimator. Experimental results are presented to verify the effectiveness of the proposed approach

Keywords

angular velocity control; asynchronous machines; electric machine analysis computing; losses; machine vector control; model reference adaptive control systems; neural nets; ANN; MRAS speed estimator; artificial neural network; flux weakening region; induction machine; iron losses; magnetic saturation; model reference adaptive system speed estimator; speed sensorless vector control; Adaptive systems; Artificial neural networks; Induction machines; Induction motors; Iron; Machine vector control; Magnetic flux; Magnetic losses; Saturation magnetization; Sensorless control;

fLanguage

English

Publisher

ieee

Conference_Titel

IEEE Industrial Electronics, IECON 2006 - 32nd Annual Conference on

Conference_Location

Paris

ISSN

1553-572X

Print_ISBN

1-4244-0390-1

Type

conf

DOI

10.1109/IECON.2006.347528

Filename

4153129