Speed Estimation of Induction Motor Using Model Reference Adaptive System with Kalman Filter

The paper deals with a speed estimation of the induction motor using observer with Model Reference Adaptive System and Kalman Filter. For simulation, Hardware in Loop Simulation method is used. The first part of the paper includes the mathematical description of the observer for the speed estimation...

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Main Authors: Pavel Brandstetter, Marek Dobrovsky
Format: Article
Language:English
Published: VSB-Technical University of Ostrava 2013-01-01
Series:Advances in Electrical and Electronic Engineering
Subjects:
Online Access:http://advances.utc.sk/index.php/AEEE/article/view/802
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author Pavel Brandstetter
Marek Dobrovsky
author_facet Pavel Brandstetter
Marek Dobrovsky
author_sort Pavel Brandstetter
collection DOAJ
description The paper deals with a speed estimation of the induction motor using observer with Model Reference Adaptive System and Kalman Filter. For simulation, Hardware in Loop Simulation method is used. The first part of the paper includes the mathematical description of the observer for the speed estimation of the induction motor. The second part describes Kalman filter. The third part describes Hardware in Loop Simulation method and its realization using multifunction card MF 624. In the last section of the paper, simulation results are shown for different changes of the induction motor speed which confirm high dynamic properties of the induction motor drive with sensorless control.
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spelling doaj.art-27dcd125200f429a99616ed6551c13352023-05-14T20:50:08ZengVSB-Technical University of OstravaAdvances in Electrical and Electronic Engineering1336-13761804-31192013-01-01111222810.15598/aeee.v11i1.802571Speed Estimation of Induction Motor Using Model Reference Adaptive System with Kalman FilterPavel Brandstetter0Marek Dobrovsky1VSB - Technical University of Ostrava Department of ElectronicsVSB - Technical University of Ostrava Department of ElectronicsThe paper deals with a speed estimation of the induction motor using observer with Model Reference Adaptive System and Kalman Filter. For simulation, Hardware in Loop Simulation method is used. The first part of the paper includes the mathematical description of the observer for the speed estimation of the induction motor. The second part describes Kalman filter. The third part describes Hardware in Loop Simulation method and its realization using multifunction card MF 624. In the last section of the paper, simulation results are shown for different changes of the induction motor speed which confirm high dynamic properties of the induction motor drive with sensorless control.http://advances.utc.sk/index.php/AEEE/article/view/802hardware in loop simulationinduction motorkalman filtermodel reference adaptive systemsensorless control.
spellingShingle Pavel Brandstetter
Marek Dobrovsky
Speed Estimation of Induction Motor Using Model Reference Adaptive System with Kalman Filter
Advances in Electrical and Electronic Engineering
hardware in loop simulation
induction motor
kalman filter
model reference adaptive system
sensorless control.
title Speed Estimation of Induction Motor Using Model Reference Adaptive System with Kalman Filter
title_full Speed Estimation of Induction Motor Using Model Reference Adaptive System with Kalman Filter
title_fullStr Speed Estimation of Induction Motor Using Model Reference Adaptive System with Kalman Filter
title_full_unstemmed Speed Estimation of Induction Motor Using Model Reference Adaptive System with Kalman Filter
title_short Speed Estimation of Induction Motor Using Model Reference Adaptive System with Kalman Filter
title_sort speed estimation of induction motor using model reference adaptive system with kalman filter
topic hardware in loop simulation
induction motor
kalman filter
model reference adaptive system
sensorless control.
url http://advances.utc.sk/index.php/AEEE/article/view/802
work_keys_str_mv AT pavelbrandstetter speedestimationofinductionmotorusingmodelreferenceadaptivesystemwithkalmanfilter
AT marekdobrovsky speedestimationofinductionmotorusingmodelreferenceadaptivesystemwithkalmanfilter