Efficient single and dual axis solar tracking system controllers based on adaptive neural fuzzy inference system

Basit Öğe Kaydı
dc.authorscopusid53879457100
dc.authorscopusid6603297760
dc.authorscopusid56069854200
dc.contributor.authorAl-Rousan, Nadia
dc.contributor.authorMat Isa, Nor Ashidi
dc.contributor.authorMat Desa, Mohd Khairunaz
dc.date.accessioned2024-09-11T19:57:35Z
dc.date.available2024-09-11T19:57:35Z
dc.date.issued2020
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description.abstractArtificial Intelligence is widely used in solar applications. Adaptive Neural Fuzzy Inference System (ANFIS) principle is one of the intelligent techniques that is sufficient to be used in control systems. This paper proposes two new efficient intelligent solar tracking control systems based on ANFIS principle. The aim of this paper is to design and implement efficient single and dual-axis solar tracking control systems that can increase the performance of solar trackers, predict the trajectory of the sun across the sky accurately, and minimize the error, therefore, maximize the energy output of solar tracking systems. Experimental data are used to train and test the proposed solar tracking controllers by using month, day and time as input variables to predict the optimum positions for solar tracking systems (tilt/orientation angles). The proposed ANFIS models have been evaluated to find its capability and robustness in tracking the optimum angles that gain the maximum solar radiation. It is found that the proposed controllers are optimum to control solar tracking systems with high prediction rate and the low error rate. Besides, the selected variables along with the selected architecture could successfully predict the optimum tilt and orientation angles. The proposed models provide superior results with five membership functions, and it could obtain high performance for both single-axis and dual-axis solar tracking systems. © 2020 The Authorsen_US
dc.identifier.doi10.1016/j.jksues.2020.04.004
dc.identifier.endpage469en_US
dc.identifier.issn1018-3639en_US
dc.identifier.issue7en_US
dc.identifier.scopus2-s2.0-85083738651en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage459en_US
dc.identifier.urihttps://doi.org/10.1016/j.jksues.2020.04.004
dc.identifier.urihttps://hdl.handle.net/11363/8312
dc.identifier.volume32en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherKing Saud Universityen_US
dc.relation.ispartofJournal of King Saud University - Engineering Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240903_Gen_US
dc.subjectAdaptive neural fuzzy inference system; Dual-axis; Fuzzy logic; Neural network; Single-axis; Solar tracking systemsen_US
dc.titleEfficient single and dual axis solar tracking system controllers based on adaptive neural fuzzy inference systemen_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
Makale / Article
Boyut:
1.34 MB
Biçim:
Adobe Portable Document Format
İndir

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu