Design and Application of Neural Network for Compensation of VSI Output Voltage Nonlinearities

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dc.contributor.authorBuchta, Luděkcs
dc.contributor.authorKozovský, Matúšcs
dc.date.accessioned2025-04-04T11:56:50Z
dc.date.available2025-04-04T11:56:50Z
dc.date.issued2024-11-03cs
dc.description.abstractVoltage source inverters (VSI) with modern power-switching elements are often used to control industrial AC motors. However, the non-linearities of the inverters, such as dead time, turn-on and turn-off switching delay times and voltage drops, are often behind the distortion of the phase currents of the controlled motor. The current distortions can be suppressed by appropriately calculated non-linear functions, which represent the compensation voltages and are consequently added to the control values of the current regulators in the field-oriented control (FOC) algorithm. An artificial neural network (ANN) was designed to identify the non-linear functions of the compensation voltages, which is presented in this paper. Only signals available in the FOC algorithm are used as ANN inputs. The learning process of the neural network takes place online during the running of the motor control algorithm. The learning pattern is generated in each step of the control algorithm from the control errors of the current controllers and the previous ANN outputs. It is not necessary to know the VSI parameters when learning the neural network. The proposed ANN and back-propagation learning algorithm were implemented on one core of the AURIX microcontroller TC397. The proposed strategy was validated through experiments on a real permanent magnet synchronous motor (PMSM), and experimental results prove the effectiveness of the ANN.en
dc.formattextcs
dc.format.extent1-6cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationIECON 2024- 50th Annual Conference of the IEEE Industrial Electronics Society. 2024, p. 1-6.en
dc.identifier.doi10.1109/IECON55916.2024.10905982cs
dc.identifier.isbn978-1-6654-6454-3cs
dc.identifier.orcid0000-0002-8954-3495cs
dc.identifier.orcid0000-0002-1547-1003cs
dc.identifier.other189973cs
dc.identifier.researcheridG-8085-2014cs
dc.identifier.researcheridE-2371-2018cs
dc.identifier.scopus56028720700cs
dc.identifier.urihttps://hdl.handle.net/11012/250792
dc.language.isoencs
dc.publisherIEEEcs
dc.relation.ispartofIECON 2024- 50th Annual Conference of the IEEE Industrial Electronics Societycs
dc.relation.urihttps://ieeexplore.ieee.org/document/10905982/authors#authorscs
dc.rights(C) IEEEcs
dc.rights.accessopenAccesscs
dc.subjectInverter nonlinearitiesen
dc.subjectArtificial neural networken
dc.subjectDead-time compensationen
dc.subjectPermanent magnet synchronous motoren
dc.titleDesign and Application of Neural Network for Compensation of VSI Output Voltage Nonlinearitiesen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionacceptedVersionen
sync.item.dbidVAV-189973en
sync.item.dbtypeVAVen
sync.item.insts2025.04.04 13:56:50en
sync.item.modts2025.04.03 13:32:06en
thesis.grantorVysoké učení technické v Brně. Středoevropský technologický institut VUT. Kybernetika a robotikacs
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