Comparison of the speedy estimate methods of the induction motors

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10251986" target="_blank" >RIV/61989100:27240/23:10251986 - isvavai.cz</a>

Výsledek na webu

<a href="http://telkomnika.uad.ac.id/index.php/TELKOMNIKA/article/view/24089" target="_blank" >http://telkomnika.uad.ac.id/index.php/TELKOMNIKA/article/view/24089</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.12928/TELKOMNIKA.v21i1.24089" target="_blank" >10.12928/TELKOMNIKA.v21i1.24089</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Comparison of the speedy estimate methods of the induction motors

Popis výsledku v původním jazyce

This paper deals with a novel method to achieve the effective performance of the extended Kalman filter (EKF) for the speedy estimate of an induction motor. The real coding genetic algorithm (GA) is used to optimize the components of the covariance matrix in the EKF, thus ensuring the stability and accuracy of the filter in the speed estimation. The advantage of the proposed method is less dependent on the parameters of the induction motor. The content includes the vector control model for induction motor, the speed estimation by modeling the reference frame-model reference adaptive system (RF-MRAS), the current based-model reference adaptive system (CB-MRAS), and the speed estimation with the EKF optimized by genetic algorithm. Simulative studies on the field-oriented controller (FOC) with different operating conditions are performed in Matlab Simulink when the rotor resistance changes in the current speed estimation methods. The simulation results demonstrate the efficiency of the proposed GA-EKF filter compared with other speed estimation methods of induction motors.

Název v anglickém jazyce

Comparison of the speedy estimate methods of the induction motors

Popis výsledku anglicky

This paper deals with a novel method to achieve the effective performance of the extended Kalman filter (EKF) for the speedy estimate of an induction motor. The real coding genetic algorithm (GA) is used to optimize the components of the covariance matrix in the EKF, thus ensuring the stability and accuracy of the filter in the speed estimation. The advantage of the proposed method is less dependent on the parameters of the induction motor. The content includes the vector control model for induction motor, the speed estimation by modeling the reference frame-model reference adaptive system (RF-MRAS), the current based-model reference adaptive system (CB-MRAS), and the speed estimation with the EKF optimized by genetic algorithm. Simulative studies on the field-oriented controller (FOC) with different operating conditions are performed in Matlab Simulink when the rotor resistance changes in the current speed estimation methods. The simulation results demonstrate the efficiency of the proposed GA-EKF filter compared with other speed estimation methods of induction motors.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

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 periodika

Telkomnika

ISSN

1693-6930

e-ISSN

2087-278X

Svazek periodika

21

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

ID - Indonéská republika

Počet stran výsledku

12

Strana od-do

223-234

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85143848913