Speed Neuro-fuzzy Estimator Applied To Sensorless Induction Motor Control


Autoria(s): Lima, F.; Kaiser, Walter; Silva, Ivan Nunes da; Oliveira Junior, Azauri Albano de
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

05/11/2013

05/11/2013

2012

Resumo

This work proposes the development of an Adaptive Neuro-fuzzy Inference System (ANFIS) estimator applied to speed control in a three-phase induction motor sensorless drive. Usually, ANFIS is used to replace the traditional PI controller in induction motor drives. The evaluation of the estimation capability of the ANFIS in a sensorless drive is one of the contributions of this work. The ANFIS speed estimator is validated in a magnetizing flux oriented control scheme, consisting in one more contribution. As an open-loop estimator, it is applied to moderate performance drives and it is not the proposal of this work to solve the low and zero speed estimation problems. Simulations to evaluate the performance of the estimator considering the vector drive system were done from the Matlab/Simulink(R) software. To determine the benefits of the proposed model, a practical system was implemented using a voltage source inverter (VSI) to drive the motor and the vector control including the ANFIS estimator, which is carried out by the Real Time Toolbox from Matlab/Simulink(R) software and a data acquisition card from National Instruments.

Identificador

IEEE LATIN AMERICA TRANSACTIONS, PISCATAWAY, v. 10, n. 5, p. 2065-2073, SEP, 2012

1548-0992

http://www.producao.usp.br/handle/BDPI/41901

10.1109/TLA.2012.6362350

http://dx.doi.org/10.1109/TLA.2012.6362350

Idioma(s)

por

Publicador

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

PISCATAWAY

Relação

IEEE LATIN AMERICA TRANSACTIONS

Direitos

closedAccess

Copyright IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Palavras-Chave #INDUCTION MOTORS #ARTIFICIAL NEURAL NETWORKS #FUZZY LOGIC #SENSORLESS DRIVES #ANFIS #DRIVES #COMPUTER SCIENCE, INFORMATION SYSTEMS #ENGINEERING, ELECTRICAL & ELECTRONIC
Tipo

article

original article

publishedVersion