NDLI: Neural network and fuzzy logic in a speed close loop for DTC induction motors

Content Provider	IEEE Xplore Digital Library
Author	Ponce, Pedro Molina, Arturo Tellez, Arturo
Copyright Year	2014
Description	Author affiliation: Departamento de Mecatronica ITESM-CCM Mexico City, Mexico (Ponce, Pedro; Molina, Arturo; Tellez, Arturo)
Abstract	Direct Torque Control (DTC) is known to produce quick and robust response in AC drives. However, during steady state, torque, flux and current ripple occur. An improvement of the electric drive can be obtained using a DTC scheme based on the Space Vector Modulation (SVM) which reduces the torque and flux ripple. The proposed control scheme considers the rotor resistance variation. This paper also discusses the application of Type-2 Fuzzy speed Control under uncertain stimuli and an Artificial Neural Network (ANN) as a speed estimator. The capability and precision of this scheme as a speed controller and estimator are verified by different conditions and it is concluded that the proposed control scheme produces good results.
Starting Page	1
Ending Page	7
File Size	1388060
Page Count	7
File Format	PDF
e-ISBN	9781479946839
DOI	10.1109/ICCDCS.2014.7016166
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-04-02
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vectors Torque Stators Induction motors Artificial neural networks Space vector pulse width modulation Fuzzy logic Type-2 Fuzzy Logic System DTC SVPWM ANN Sensorless
Content Type	Text
Resource Type	Article

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