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A comparison of induction motor speed estimation using conventional MRAS and AI-based MRAS with a dynamic reference model

Lookup NU author(s): Emeritus Professor John Finch

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Abstract

The Model Reference Adaptive System (MRAS) is probably the most widely applied speed sensorless drive control scheme. This paper compares induction motor speed estimation using conventional MRAS and AI-based MRAS with Stator Resistance Compensation. A conventional mathematical model based MRAS speed estimation scheme can give a relatively precise speed estimation result, but errors will occur during low frequency operation. Furthermore, it is also very sensitive to machine parameter variations. However, an AI-based MRAS-based system with a Stator Resistance Compensation model can improve the speed estimation accuracy and is relatively robust to parameter variations even at an extremely low frequency. Simulation results using a validated machine model are used to demonstrate the improved behaviour.


Publication metadata

Author(s): Yang C, Finch JW

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: World Congress on Engineering (WCE 2008)

Year of Conference: 2008

Pages: 375-380

ISSN: 9789889867195

Publisher: International Association of Engineers

Library holdings: Search Newcastle University Library for this item

Series Title: Lecture notes in engineering and computer science

ISBN:


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