Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5640
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dc.contributor.authorEfe, Mehmet Önder-
dc.contributor.authorDebiasi M.-
dc.contributor.authorYan Peng-
dc.contributor.authorÖzbay Hitay-
dc.contributor.authorSamimy Mohammad-
dc.date.accessioned2021-09-11T15:19:28Z-
dc.date.available2021-09-11T15:19:28Z-
dc.date.issued2005en_US
dc.identifier.citation43rd AIAA Aerospace Sciences Meeting and Exhibit, 10 January 2005 through 13 January 2005, Reno, NV, 66366en_US
dc.identifier.urihttps://doi.org/10.2514/6.2005-294-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/5640-
dc.description.abstractFlow control is attracting an increasing attention of researchers from a wide spectrum of specialties because of its interdisciplinary nature and the associated challenges. One of the main goals of The Collaborative Center of Control Science at The Ohio State University is to bring together researchers from different disciplines to advance the science and technology of flow control. This paper approaches the control of subsonic cavity flow, a study case we have selected, from a computational intelligence point of view, and offers a solution that displays an interconnected neural architecture. The structures of identification and control, together with the experimental implementation are discussed. The model and the controller have very simple structural configurations indicating that a significant saving on computation is possible. Experimental testing of a neural emulator and of a directly-synthesized neurocontroller indicates that the emulator can accurately reproduce a reference signal measured in the cavity floor under different operating conditions. Based on preliminary results, the neurocontroller appears to be marginally effective and produces spectral peak reductions analogous to those previously observed by the authors using linearcontrol techniques. The current research will continue to improve the capability of the neural emulator and of the neurocontroller.en_US
dc.description.sponsorshipAmerican Institute of Aeronautics and Astronautics, AIAAen_US
dc.language.isoenen_US
dc.publisherAmerican Institute of Aeronautics and Astronautics Inc.en_US
dc.relation.ispartof43rd AIAA Aerospace Sciences Meeting and Exhibit - Meeting Papersen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleControl of Subsonic Cavity Flows by Neural Networks -Analytical Models and Experimental Validationen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.identifier.startpage6441en_US
dc.identifier.endpage6454en_US
dc.identifier.scopus2-s2.0-30744476240en_US
dc.institutionauthorÖnder Efe, Mehmet-
dc.identifier.doi10.2514/6.2005-294-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conference43rd AIAA Aerospace Sciences Meeting and Exhibiten_US
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.5. Department of Electrical and Electronics Engineering-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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