Artificial neural network-based discrete-fuzzy logic controlled active power filter

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dc.authoridTumay, Mehmet/0000-0002-6055-3761
dc.authoridteke, ahmet/0000-0003-2610-9576
dc.authoridSARIBULUT, LUTFU/0000-0002-6183-9550
dc.contributor.authorSaribulut, Lutfu
dc.contributor.authorTeke, Ahmet
dc.contributor.authorTumay, Mehmet
dc.date.accessioned2025-01-06T17:44:57Z
dc.date.available2025-01-06T17:44:57Z
dc.date.issued2014
dc.description.abstractArtificial neural network (ANN) is a computational algorithm based on the structure and functions of biological neural networks. It is used for modelling of the non-linear systems that cannot be mathematically expressed by the formula and extraction of the system dynamics, expressed by using the complex mathematical equations, such as harmonics. To show the effective usage of ANNs in the power system, the fundamental harmonic of a load with six-pulse thyristor controlled rectifier is extracted with ANN by using the system variables that are difficult to express with each other. Then, a new approach is proposed to generate the reference signal for compensating the harmonics of the current by using discrete fuzzy logic in this study. In addition, a simple and useful method to determine the circuit parameters of the active power filter (APF) is proposed to reduce the rating of the required filter and the capacitor values without affecting its efficiency. Case studies are performed to test the performance of the proposed control algorithm for APF.
dc.identifier.doi10.1049/iet-pel.2013.0522
dc.identifier.endpage1546
dc.identifier.issn1755-4535
dc.identifier.issn1755-4543
dc.identifier.issue6
dc.identifier.scopus2-s2.0-84929464483
dc.identifier.scopusqualityQ2
dc.identifier.startpage1536
dc.identifier.urihttps://doi.org/10.1049/iet-pel.2013.0522
dc.identifier.urihttps://hdl.handle.net/20.500.14669/3258
dc.identifier.volume7
dc.identifier.wosWOS:000337955500021
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInst Engineering Technology-Iet
dc.relation.ispartofIet Power Electronics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectExtractıon
dc.subjectHarmonıcs
dc.subjectSystem
dc.subjectClassıfıcatıon
dc.subjectModulatıon
dc.subjectWındow
dc.titleArtificial neural network-based discrete-fuzzy logic controlled active power filter
dc.typeArticle

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