Application of Optimal Solutions in Field-Oriented Control of Induction Motor

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10254432" target="_blank" >RIV/61989100:27240/23:10254432 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.intechopen.com/chapters/1134665" target="_blank" >https://www.intechopen.com/chapters/1134665</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5772/intechopen.1001609" target="_blank" >10.5772/intechopen.1001609</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Application of Optimal Solutions in Field-Oriented Control of Induction Motor

Popis výsledku v původním jazyce

This chapter presents the optimal solutions in field-oriented control for induction motors. It includes the introduction of the Genetic Algorithm (GA), Particle Swarm Optimizer (PSO), and Cuckoo Search Algorithm (CSA). In those algorithms, the GA algorithm is used to control the speed of the induction motor. With the GA algorithm, the speed response of the induction motor always achieves good stability in the case of no-load and under-load. This chapter also presents the optimal parameter search of the PID controller, such as proportional factor (Kp), integral coefficient (Ki), and differential coefficient (Kd), by the genetic algorithm. Finally, the simulation results on Matlab Simulink and the experimental results on TI&apos;s DSP 82335 have demonstrated the advantages of the proposed methods compared to the traditional PID methods.

Název v anglickém jazyce

Application of Optimal Solutions in Field-Oriented Control of Induction Motor

Popis výsledku anglicky

This chapter presents the optimal solutions in field-oriented control for induction motors. It includes the introduction of the Genetic Algorithm (GA), Particle Swarm Optimizer (PSO), and Cuckoo Search Algorithm (CSA). In those algorithms, the GA algorithm is used to control the speed of the induction motor. With the GA algorithm, the speed response of the induction motor always achieves good stability in the case of no-load and under-load. This chapter also presents the optimal parameter search of the PID controller, such as proportional factor (Kp), integral coefficient (Ki), and differential coefficient (Kd), by the genetic algorithm. Finally, the simulation results on Matlab Simulink and the experimental results on TI&apos;s DSP 82335 have demonstrated the advantages of the proposed methods compared to the traditional PID methods.

Druh

C - Kapitola v odborné knize

CEP obor

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OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Induction Motors - Recent Advances, New Perspectives and Applications

ISBN

978-1-83769-576-8

Počet stran výsledku

21

Strana od-do

1-21

Počet stran knihy

222

Název nakladatele

IntechOpen

Místo vydání

Londýn

Kód UT WoS kapitoly

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