Toggle Main Menu Toggle Search

Open Access padlockePrints

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


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


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