Series load induction heating inverter state estimator using Kalman filter

LQR and H2 controllers require access to the states of the controlled system. The method based on description function with Fourier series results in a model with immeasurable states. For this reason, we proposed a Kalman filter based state estimator, which not only filters the input signals, but al...

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Main Authors: Szelitzky T., A.O. Neaga, M. Tulbure, C. Filip, Both R.
Format: Article
Language:English
Published: Editura Universităţii "Petru Maior" 2011-12-01
Series:Scientific Bulletin of the ''Petru Maior" University of Tîrgu Mureș
Subjects:
Online Access:http://scientificbulletin.upm.ro/papers/2011/12/Szelitzky-T.-Neaga-A.O.-Tulbure-M.-Filip-C.-Both-R.-Series-load-induction-heating-inverter-state-estimator-using-Kalman-filter1.pdf
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author Szelitzky T.
A.O. Neaga
M. Tulbure
C. Filip
Both R.
author_facet Szelitzky T.
A.O. Neaga
M. Tulbure
C. Filip
Both R.
author_sort Szelitzky T.
collection DOAJ
description LQR and H2 controllers require access to the states of the controlled system. The method based on description function with Fourier series results in a model with immeasurable states. For this reason, we proposed a Kalman filter based state estimator, which not only filters the input signals, but also computes the unobservable states of the system. The algorithm of the filter was implemented in LabVIEW v8.6 and tested on recorded data obtained from a 10-40 kHz series load frequency controlled induction heating inverter.
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spelling doaj.art-1b130b1f6ddb4f11a0dd148fd92292312022-12-21T23:35:54ZengEditura Universităţii "Petru Maior"Scientific Bulletin of the ''Petru Maior" University of Tîrgu Mureș1841-92672285-438X2011-12-018 (XXV)26265Series load induction heating inverter state estimator using Kalman filterSzelitzky T.A.O. NeagaM. TulbureC. FilipBoth R.LQR and H2 controllers require access to the states of the controlled system. The method based on description function with Fourier series results in a model with immeasurable states. For this reason, we proposed a Kalman filter based state estimator, which not only filters the input signals, but also computes the unobservable states of the system. The algorithm of the filter was implemented in LabVIEW v8.6 and tested on recorded data obtained from a 10-40 kHz series load frequency controlled induction heating inverter.http://scientificbulletin.upm.ro/papers/2011/12/Szelitzky-T.-Neaga-A.O.-Tulbure-M.-Filip-C.-Both-R.-Series-load-induction-heating-inverter-state-estimator-using-Kalman-filter1.pdfInduction heatingKalman state estimator
spellingShingle Szelitzky T.
A.O. Neaga
M. Tulbure
C. Filip
Both R.
Series load induction heating inverter state estimator using Kalman filter
Scientific Bulletin of the ''Petru Maior" University of Tîrgu Mureș
Induction heating
Kalman state estimator
title Series load induction heating inverter state estimator using Kalman filter
title_full Series load induction heating inverter state estimator using Kalman filter
title_fullStr Series load induction heating inverter state estimator using Kalman filter
title_full_unstemmed Series load induction heating inverter state estimator using Kalman filter
title_short Series load induction heating inverter state estimator using Kalman filter
title_sort series load induction heating inverter state estimator using kalman filter
topic Induction heating
Kalman state estimator
url http://scientificbulletin.upm.ro/papers/2011/12/Szelitzky-T.-Neaga-A.O.-Tulbure-M.-Filip-C.-Both-R.-Series-load-induction-heating-inverter-state-estimator-using-Kalman-filter1.pdf
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AT aoneaga seriesloadinductionheatinginverterstateestimatorusingkalmanfilter
AT mtulbure seriesloadinductionheatinginverterstateestimatorusingkalmanfilter
AT cfilip seriesloadinductionheatinginverterstateestimatorusingkalmanfilter
AT bothr seriesloadinductionheatinginverterstateestimatorusingkalmanfilter