A Hybrid Differential Artificial Bee Colony Algorithm based tuning of fractional order controller for Permanent Magnet Synchronous Motor drive
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092822" target="_blank" >RIV/61989100:27240/14:86092822 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s13042-012-0136-2" target="_blank" >http://dx.doi.org/10.1007/s13042-012-0136-2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s13042-012-0136-2" target="_blank" >10.1007/s13042-012-0136-2</a>
Alternative languages
Result language
angličtina
Original language name
A Hybrid Differential Artificial Bee Colony Algorithm based tuning of fractional order controller for Permanent Magnet Synchronous Motor drive
Original language description
In this paper a novel Hybrid Differential Artificial Bee Colony Algorithm (HDABCA) has been proposed for designing a fractional order proportional-integral (FO-PI) speed controller in a Permanent Magnet Synchronous Motor (PMSM) drive. FO-PI controllers'parameters involve proportionality constant, integral constant and integral order, and hence its design is more complex than that of the usual Integral-order proportional-integral controller. To overcome this complexity in designing, we had used the proposed hybrid algorithm, such that all the design specifications of the motor are satisfied. In order to digitally realize the FO-PI controller, an Oustaloup approximation method has been used. Simulations and comparisons of proposed HDABCA with conventional methods and also other state-of-art methods demonstrate the competence of the proposed approach, especially for actuating fractional order controller for integer order plants. 2012 Springer-Verlag Berlin Heidelberg.
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
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Machine Learning and Cybernetics
ISSN
1868-8071
e-ISSN
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Volume of the periodical
5
Issue of the periodical within the volume
3
Country of publishing house
DE - GERMANY
Number of pages
11
Pages from-to
327-337
UT code for WoS article
000348040100001
EID of the result in the Scopus database
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