Toggle Main Menu Toggle Search

Open Access padlockePrints

The Newcastle University research output collection, currently available on ePrints, will shortly be moving to a new open repository platform, Figshare. To prepare for the data migration we have paused adding new content to ePrints, and will resume once the new repository is launched. During this time you will continue to have access to ePrints (but no new content will appear). We will share updates here when available.

An Experimental Assessment of a Stator Current MRAS Based on Neural Networks for Sensorless Control of Induction Machines

Lookup NU author(s): Dr Shady Gadoue, Professor Damian GiaourisORCiD, Emeritus Professor John Finch

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.

Abstract

In this paper an experimental evaluation of a novel Model Reference Adaptive System (MRAS) speed observer for induction motor drives based on stator currents is presented. In this scheme the measured stator currents are used as the reference model for the MRAS observer to avoid the use of a pure integrator. A two-layer Neural Network (NN) stator current observer is used as the adaptive model which requires the rotor flux information that can be obtained from the current model. Speed estimation performance of the new MRAS scheme is studied and compared with the classical rotor flux MRAS when applied to an indirect vector control induction motor drive. Experimental results are shown for the two schemes in the low speed region of operation including tests for the regenerating mode. These results complement the simulation results presented for the proposed scheme in a recent work.

Publication metadata

Author(s): Gadoue SM, Giaouris D, Finch JW

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Symposium on Sensorless Control for Electrical Drives (SLED)

Year of Conference: 2011

Pages: 102-106

Publisher: IEEE

URL: http://dx.doi.org/10.1109/SLED.2011.6051552

Library holdings: Search Newcastle University Library for this item

ISBN: 9781457718557

Share