Sensorless control of variable speed induction motor drive using RBF neural network

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238428" target="_blank" >RIV/61989100:27240/17:10238428 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.jal.2016.11.017" target="_blank" >http://dx.doi.org/10.1016/j.jal.2016.11.017</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jal.2016.11.017" target="_blank" >10.1016/j.jal.2016.11.017</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Sensorless control of variable speed induction motor drive using RBF neural network

Popis výsledku v původním jazyce

High power of modern digital signal processors and their decreasing prices enable practical implementation of different speed estimators which are used in the sensorless control of AC drives. The paper describes application possibilities of artificial neural networks for the sensorless speed control of the A.C. induction motor drive. In the sensorless control structure of the A.C. drive, there is implemented the speed estimator which uses two different artificial neural networks for speed estimation. The first speed estimator uses a multilayer feedforward artificial neural network. Its properties are compared with the speed estimator using a radial basis function neural network. The sensorless A.C. drive was simulated in program Matlab-Simulink. The main goal of many simulations was finding suitable structure of the artificial neural network with required number of neuron units which will ensure good control characteristics and simultaneously will enable a practical implementation of the artificial neural network in the digital signal processor control system.

Název v anglickém jazyce

Sensorless control of variable speed induction motor drive using RBF neural network

Popis výsledku anglicky

High power of modern digital signal processors and their decreasing prices enable practical implementation of different speed estimators which are used in the sensorless control of AC drives. The paper describes application possibilities of artificial neural networks for the sensorless speed control of the A.C. induction motor drive. In the sensorless control structure of the A.C. drive, there is implemented the speed estimator which uses two different artificial neural networks for speed estimation. The first speed estimator uses a multilayer feedforward artificial neural network. Its properties are compared with the speed estimator using a radial basis function neural network. The sensorless A.C. drive was simulated in program Matlab-Simulink. The main goal of many simulations was finding suitable structure of the artificial neural network with required number of neuron units which will ensure good control characteristics and simultaneously will enable a practical implementation of the artificial neural network in the digital signal processor control system.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

<a href="/cs/project/TE02000103" target="_blank" >TE02000103: Centrum inteligentních pohonů a pokročilého řízení strojů (CIDAM)</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

Journal of Applied Logic

ISSN

1570-8683

e-ISSN

—

Svazek periodika

24

Číslo periodika v rámci svazku

November 2017

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

12

Strana od-do

97-108

Kód UT WoS článku

000413130000010

EID výsledku v databázi Scopus

2-s2.0-85006991047