Selected Applications of Artificial Neural Networks in the Control of AC Induction Motor Drives
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86080421" target="_blank" >RIV/61989100:27240/11:86080421 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Selected Applications of Artificial Neural Networks in the Control of AC Induction Motor Drives
Original language description
Numerous advances have been made in developing intelligent systems, some inspired by biological neural networks. Researchers from many scientific disciplines are designing artificial neural networks to solve a variety of problems in pattern recognition,prediction, optimization and control. Conventional approaches have been proposed for solving these problems. Although successful applications can be found in certain well-constrained environments, none is flexible enough to perform well outside its domain. Artificial neural networks provide exciting alternatives, and many applications could benefit from using them. The paper deals with selected applications of artificial neural networks in the control of AC drives with induction motors, for example ANN-based vector pulse-width modulation and sensorless control of the induction motor drive using ANN.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JA - Electronics and optoelectronics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Review on Modelling and Simulations
ISSN
1974-9821
e-ISSN
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Volume of the periodical
4
Issue of the periodical within the volume
3
Country of publishing house
IT - ITALY
Number of pages
10
Pages from-to
1084-1093
UT code for WoS article
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EID of the result in the Scopus database
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