A novel hybrid ABF-PSO algorithm based tuning of optimal FOPI speed controller for PMSM drive

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86085193" target="_blank" >RIV/61989100:27240/11:86085193 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/CarpathianCC.2011.5945872" target="_blank" >http://dx.doi.org/10.1109/CarpathianCC.2011.5945872</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CarpathianCC.2011.5945872" target="_blank" >10.1109/CarpathianCC.2011.5945872</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A novel hybrid ABF-PSO algorithm based tuning of optimal FOPI speed controller for PMSM drive

Popis výsledku v původním jazyce

Bacterial Foraging Optimization algorithm (BFOA) has recently emerged as a very powerful technique for real parameter optimization. One of the major driving forces of BFOA is the chemotactic movement of a virtual bacterium that models a trial solution ofoptimization process. In the classical BFOA proposed by Passino, during the process of chemotaxis, optimization depends on a random search direction which may lead to delay in reaching global solution. To accelerate the convergence speed of group of bacteria near global optima the chemotactic step has been made adaptive and the resultant is Adaptive Bacterial Foraging Optimization (ABFO). In order to overcome the delay in optimization and to further enhance the performance of ABFO, this paper proposeda new hybrid algorithm combining the features of Adaptive Bacterial Foraging (ABF) and Particle Swarm Optimization (PSO) for tuning a Fractional order Proportional Integral speed controller in a vector controlled Permanent Magnet Synchron

Název v anglickém jazyce

A novel hybrid ABF-PSO algorithm based tuning of optimal FOPI speed controller for PMSM drive

Popis výsledku anglicky

Bacterial Foraging Optimization algorithm (BFOA) has recently emerged as a very powerful technique for real parameter optimization. One of the major driving forces of BFOA is the chemotactic movement of a virtual bacterium that models a trial solution ofoptimization process. In the classical BFOA proposed by Passino, during the process of chemotaxis, optimization depends on a random search direction which may lead to delay in reaching global solution. To accelerate the convergence speed of group of bacteria near global optima the chemotactic step has been made adaptive and the resultant is Adaptive Bacterial Foraging Optimization (ABFO). In order to overcome the delay in optimization and to further enhance the performance of ABFO, this paper proposeda new hybrid algorithm combining the features of Adaptive Bacterial Foraging (ABF) and Particle Swarm Optimization (PSO) for tuning a Fractional order Proportional Integral speed controller in a vector controlled Permanent Magnet Synchron

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of 12th International Carpathian Control Conference ICCC´ 2011

ISBN

978-1-61284-359-9

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

320-325

Název nakladatele

Institute of Electrical and Electronics Engineers

Místo vydání

New York

Místo konání akce

Velké Karlovice

Datum konání akce

25. 5. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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