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dc.contributor.authorKoleva, Radmilaen_US
dc.contributor.authorM. Lazarevska, Anaen_US
dc.contributor.authorBabunski, Darkoen_US
dc.date.accessioned2023-05-15T18:38:31Z-
dc.date.available2023-05-15T18:38:31Z-
dc.date.issued2022-05-27-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/26482-
dc.description.abstract<jats:p>In this paper, the behavior of a system dynamics is represented where neuro-controller is designed, trained, and implemented. The development of the mathematical models is based on suggestions and recommendations from the literature issued by the working group of IEEE. According to the mathematical models, simulation is developed in Simulink software. MATLAB/Simulink software was used to represent the difference between the conventional PID controller and artificial neural network (ANN) neuro-controller. Nonlinear autoregressive-moving average (NARMA-L2) has been used for control simulation of the hydro-power plant (HPP) with neuro-controllers on one hand, and conventional PID control on the other hand.</jats:p>en_US
dc.language.isoenen_US
dc.publisherAssociation for Information Communication Technology Education and Science (UIKTEN)en_US
dc.relation.ispartofTEM Journalen_US
dc.titleArtificial Neural Network-based Neurocontroller for Hydropower Plant Controlen_US
dc.typeJournal Articleen_US
dc.identifier.doi10.18421/tem112-02-
dc.identifier.urlhttps://www.temjournal.com/content/112/TEMJournalMay2022_506_512.pdf-
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Mechanical Engineering-
Appears in Collections:Faculty of Mechanical Engineering: Journal Articles
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