Publication:
An adaptive neuro-fuzzy inference system employed cuk converter for PV applications

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dc.citedby1
dc.contributor.authorPriyadarshi N.en_US
dc.contributor.authorPadmanaban S.en_US
dc.contributor.authorHolm-Nielsen J.B.en_US
dc.contributor.authorRamachandaramurthy V.K.en_US
dc.contributor.authorBhaskar M.S.en_US
dc.contributor.authorid57195679733en_US
dc.contributor.authorid18134802000en_US
dc.contributor.authorid14421042300en_US
dc.contributor.authorid6602912020en_US
dc.contributor.authorid56229894300en_US
dc.date.accessioned2023-05-29T07:26:00Z
dc.date.available2023-05-29T07:26:00Z
dc.date.issued2019
dc.descriptionAdaptive control systems; Computer circuits; DC-DC converters; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Inference engines; Power electronics; Solar radiation; Adaptive neuro-fuzzy inference system; D-space; Fuzzy logic control; Optimal power points; Photovoltaic; Fuzzy inferenceen_US
dc.description.abstractAn Adaptive Neuro-Fuzzy Inference System based Intelligent Algorithm for Photovoltaic (PV) application proposed in this paper. Under the nonlinear behavior of the surroundings, the proposed algorithm achieves optimal power point (OPP) without prior system knowledge. Compared with other intelligent methodologies, the proposed algorithm has low implementation cost, as it does not need any sensors to measure solar irradiance. The proposed algorithm provides proper training to the PV system under varying PV insolation. Modeled Cuk converter employed PV system is validate by simulated responses present in the paper. Inverter with Fuzzy logic control (FLC)-dSPACE board is also implement for sinusoidal current injection to the utility grid. � 2019 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo8862398
dc.identifier.doi10.1109/CPE.2019.8862398
dc.identifier.scopus2-s2.0-85074164391
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85074164391&doi=10.1109%2fCPE.2019.8862398&partnerID=40&md5=a2be4f42c7e646d0cb2cf6cd41448741
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24699
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleProceedings - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering, CPE-POWERENG 2019
dc.titleAn adaptive neuro-fuzzy inference system employed cuk converter for PV applicationsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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