Estimador Neuro-Fuzzy de Velocidade Aplicado ao Controle "Sensorless" de Motor de Indução (Speed Neuro-fuzzy Estimator Applied To Sensorless Induction Motor Control)

Fabio Lima (, Walter Kaiser (, Ivan Nunes da Silva (, Azauri Albano de Oliveira (

1Centro Universitário da FEI
2Universidade de São Paulo (USP) - Escola Politécnica
3Universidade de São Paulo (USP) - Escola de Engenharia de São Carlos

This paper appears in: Revista IEEE América Latina

Publication Date: Sept. 2012
Volume: 10,   Issue: 5 
ISSN: 1548-0992

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 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 software and a data acquisition card from National Instruments.

Index Terms:
induction motors, artificial neural networks, fuzzy logic, sensorless drives, ANFIS   

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