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dc.contributor.authorEfe, M. Ö.en_US
dc.contributor.authorDebiasi, M.en_US
dc.contributor.authorYan, P.en_US
dc.contributor.authorÖzbay, Hitayen_US
dc.contributor.authorSamimy, M.en_US
dc.coverage.spatialReno, Nevadaen_US
dc.date.accessioned2016-02-08T11:50:44Zen_US
dc.date.available2016-02-08T11:50:44Zen_US
dc.date.issued2005en_US
dc.identifier.urihttp://hdl.handle.net/11693/27328en_US
dc.descriptionDate of Conference: 10-13 January 2005en_US
dc.descriptionConference Name: 43rd AIAA Aerospace Sciences Meeting and Exhibit, AIAA 2005en_US
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.language.isoEnglishen_US
dc.source.titleProceedings of the 43rd AIAA Aerospace Sciences Meeting and Exhibit, AIAA 2005en_US
dc.relation.isversionofhttps://doi.org/10.2514/6.2005-294en_US
dc.subjectNeural architectureen_US
dc.subjectNeural emulatoren_US
dc.subjectNeurocontrollersen_US
dc.subjectSubsonic cavity flowen_US
dc.subjectComputational methodsen_US
dc.subjectControl equipmenten_US
dc.subjectNeural networksen_US
dc.subjectSubsonic flowen_US
dc.titleControl of subsonic cavity flows by neural networks-analytical models and experimental validationen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage1en_US
dc.citation.epage14en_US
dc.identifier.doi10.2514/6.2005-294en_US
dc.publisherAmerican Institute of Aeronautics and Astronauticsen_US
dc.contributor.bilkentauthorÖzbay, Hitay


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