A Direct Adaptive Vector Neural Control of a Three-Phase Induction Motor

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1. Verfasser: Ieroham S. Baruch
Format: Artículo científico
Sprache:en
Veröffentlicht: Instituto Politécnico Nacional 2009
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author Ieroham S. Baruch
author_facet Ieroham S. Baruch
contents A Direct Adaptive Vector Neural Control of a Three-Phase Induction Motor Ieroham S. Baruch Irving Pavel de-la-Cruz Ingeniería Levenberg Induction Motor Neural Networks Backpropagation Marquardt Learning The paper proposes a complete neural solution to the direct vector control of three phase induction motor including realtime trained neural controllers for velocity, flux and torque, which permitted the speed up reaction to the variable load. The basic equations and elements of the direct field oriented control scheme are given. The control scheme is realized by nine feedforward neural networks learned by real-time Backpropagation or off-line Levenberg-Marquardt algorithms with data taken by PI-control simulations. The graphical results of modelling show a better performance of the neural control system with respect to the PI controlled system realizing the same general control scheme. 2009 artículo científico 1665-0654 https://www.redalyc.org/articulo.oa?id=61412466005 en http://www.redalyc.org/revista.oa?id=614 Científica application/pdf Instituto Politécnico Nacional Científica (México) Num.4 Vol.13
format Artículo científico
id redalyc_61412466005
institution Redalyc
language en
publishDate 2009
publisher Instituto Politécnico Nacional
spellingShingle A Direct Adaptive Vector Neural Control of a Three-Phase Induction Motor
Ieroham S. Baruch
Ingeniería
Levenberg
Induction Motor
Neural Networks
Backpropagation
Marquardt Learning
A Direct Adaptive Vector Neural Control of a Three-Phase Induction Motor Ieroham S. Baruch Irving Pavel de-la-Cruz Ingeniería Levenberg Induction Motor Neural Networks Backpropagation Marquardt Learning The paper proposes a complete neural solution to the direct vector control of three phase induction motor including realtime trained neural controllers for velocity, flux and torque, which permitted the speed up reaction to the variable load. The basic equations and elements of the direct field oriented control scheme are given. The control scheme is realized by nine feedforward neural networks learned by real-time Backpropagation or off-line Levenberg-Marquardt algorithms with data taken by PI-control simulations. The graphical results of modelling show a better performance of the neural control system with respect to the PI controlled system realizing the same general control scheme. 2009 artículo científico 1665-0654 https://www.redalyc.org/articulo.oa?id=61412466005 en http://www.redalyc.org/revista.oa?id=614 Científica application/pdf Instituto Politécnico Nacional Científica (México) Num.4 Vol.13
title A Direct Adaptive Vector Neural Control of a Three-Phase Induction Motor
topic Ingeniería
Levenberg
Induction Motor
Neural Networks
Backpropagation
Marquardt Learning
url https://www.redalyc.org/articulo.oa?id=61412466005