Real Time Selective Harmonic Control - PWM Based on Artificial Neural Networks

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dc.contributor.authorIbanez-Hidalgo, Irati
dc.contributor.authorSanchez-Ruiz, Alain
dc.contributor.authorPerez-Basante, Angel
dc.contributor.authorZubizarreta, Asier
dc.contributor.authorCeballos, Salvador
dc.contributor.authorGil-Lopez, Sergio
dc.contributor.authorAguilera, Ricardo P.
dc.contributor.institutionPOWER ELECTRONICS AND SYSTEM EQUIPMENT
dc.contributor.institutionIA
dc.date.accessioned2024-07-24T12:00:09Z
dc.date.available2024-07-24T12:00:09Z
dc.date.issued2024-01-01
dc.descriptionPublisher Copyright: © 1986-2012 IEEE.
dc.description.abstractSelective harmonic elimination-pulse width modulation (SHE-PWM) is a widely used low switching frequency modulation technique for medium-voltage high-power converters. This approach is able to adjust the converter fundamental component while eliminating low-order harmonics. However, some applications such as active power filters (APFs) require regulating simultaneously, both the fundamental and low-order harmonics in amplitude and phase. This article presents a novel selective harmonic control-PWM (SHC-PWM) modulator, valid for APFs, based on artificial neural networks (ANNs) and sequential quadratic programming (SQP). A new offline search methodology, based on a hybrid metaheuristic-numerical algorithm, is defined to calculate the solution space when both the fundamental and a low-order harmonic are controlled in phase and amplitude. The solutions obtained are used to train the ANNs offline. Afterwards, the ANN + SQP calculation method is used to solve the SHC-PWM problem in real-time (RT). Experimental results are provided for a three-level converter to verify the effectiveness of the proposed RT control method.en
dc.description.statusPeer reviewed
dc.format.extent16
dc.identifier.citationIbanez-Hidalgo , I , Sanchez-Ruiz , A , Perez-Basante , A , Zubizarreta , A , Ceballos , S , Gil-Lopez , S & Aguilera , R P 2024 , ' Real Time Selective Harmonic Control - PWM Based on Artificial Neural Networks ' , IEEE Transactions on Power Electronics , vol. 39 , no. 1 , pp. 768-783 . https://doi.org/10.1109/TPEL.2023.3322500
dc.identifier.doi10.1109/TPEL.2023.3322500
dc.identifier.issn0885-8993
dc.identifier.urihttps://hdl.handle.net/11556/3016
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85174816923&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofIEEE Transactions on Power Electronics
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsActive power filter (APF)
dc.subject.keywordsartificial neural network (ANN)
dc.subject.keywordsmetaheuristic algorithm
dc.subject.keywordsnumerical algorithm
dc.subject.keywordsreal-time (RT)
dc.subject.keywordsselective harmonic control (SHC-PWM)
dc.subject.keywordsElectrical and Electronic Engineering
dc.titleReal Time Selective Harmonic Control - PWM Based on Artificial Neural Networksen
dc.typejournal article
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