A neural-network-based space-vector PWM controller for voltage-fed inverter induction motor drive

Joao O.P. Pinto; Bimal K. Bose; Luiz Eduardo Borges Da Silva; Marian P. Kazmierkowski

doi:10.1109/28.887215

A neural-network-based space-vector PWM controller for voltage-fed inverter induction motor drive

Joao O.P. Pinto, Bimal K. Bose, Luiz Eduardo Borges Da Silva, Marian P. Kazmierkowski

Research output: Contribution to journal › Article › peer-review

134 Scopus citations

Abstract

A neural-network-based implementation of space-vector modulation (SVM) of a voltage-fed inverter has been proposed in this paper that fully covers the undermodulation and overmodulation regions linearly extending operation smoothly up to square wave. A neural network has the advantage of very fast implementation of an SVM algorithm that can increase the converter switching frequency, particularly when a dedicated application-specific integrated circuit chip is used in the modulator. The scheme has been fully implemented and extensively evaluated in a V/Hz-controlled 5-hp 60-Hz 230-V induction motor drive. The performances of the drive with artificial-neural-network-based SVM are excellent. The scheme can be easily extended to a vector-controlled drive.

Original language	English
Pages (from-to)	1628-1636
Number of pages	9
Journal	IEEE Transactions on Industry Applications
Volume	36
Issue number	6
DOIs	https://doi.org/10.1109/28.887215
State	Published - 2000
Externally published	Yes

Funding

Paper IPCSD 00–036, presented at the 1999 Industry Applications Society Annual Meeting, Phoenix, AZ, October 3–7, and approved for publication in the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the Industrial Drives Committee of the IEEE Industry Applications Society. Manuscript submitted for review October 15, 1999 and released for publication July 17, 2000. This work was supported in part by the U.S.–Poland MSC Joint Fund II of Poland and CAPES of Brazil.

Funders	Funder number
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Keywords

Drive
Induction motor
Neural network
Pulsewidth modulation

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10.1109/28.887215

Cite this

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AB - A neural-network-based implementation of space-vector modulation (SVM) of a voltage-fed inverter has been proposed in this paper that fully covers the undermodulation and overmodulation regions linearly extending operation smoothly up to square wave. A neural network has the advantage of very fast implementation of an SVM algorithm that can increase the converter switching frequency, particularly when a dedicated application-specific integrated circuit chip is used in the modulator. The scheme has been fully implemented and extensively evaluated in a V/Hz-controlled 5-hp 60-Hz 230-V induction motor drive. The performances of the drive with artificial-neural-network-based SVM are excellent. The scheme can be easily extended to a vector-controlled drive.

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A neural-network-based space-vector PWM controller for voltage-fed inverter induction motor drive

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