Flow control refers to the ability to manipulate fluid flow so as to achieve a desired change in its behavior, which offers many potential technological benefits, such as reducing fuel costs for vehicles and improving effectiveness of industrial processes. Presently there is a lack of sufficient mathematical analysis and control design tools for flow control problems. This includes mathematical models that are amenable to control design. The research presented in this book makes an effort at closing this gap by 1) presenting a reduced-order modeling method utilizing a novel technique for input separation on Proper Orthogonal Decomposition (POD)/Galerkin Projection (GP) based models, 2) introducing a technique based on averaging theory and center manifold theory so as to reveal certain structures embedded in the model, and 3) developing nonlinear analysis and control design approaches for the resulting model. The theory is complemented by examples and case studies as appropriate, including the case of cavity flow control.
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Flow control refers to the ability to manipulate fluid flow so as to achieve a desired change in its behavior, which offers many potential technological benefits, such as reducing fuel costs for vehicles and improving effectiveness of industrial processes. Presently there is a lack of sufficient mathematical analysis and control design tools for flow control problems. This includes mathematical models that are amenable to control design. The research presented in this book makes an effort at closing this gap by 1) presenting a reduced-order modeling method utilizing a novel technique for input separation on Proper Orthogonal Decomposition (POD)/Galerkin Projection (GP) based models, 2) introducing a technique based on averaging theory and center manifold theory so as to reveal certain structures embedded in the model, and 3) developing nonlinear analysis and control design approaches for the resulting model. The theory is complemented by examples and case studies as appropriate, including the case of cavity flow control.
Dr. Co¿ku Kasnako¿lu is a faculty member with the Department of Electrical and Electronics Engineering at TOBB University of Economics and Technology in Ankara, Turkey. His research interests include reduced order modeling, nonlinear analysis and control design for flow control problems.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Flow control refers to the ability to manipulatefluid flow so as to achieve a desired change in itsbehavior, which offers many potential technologicalbenefits, such as reducing fuel costs for vehiclesand improving effectiveness of industrial processes.Presently there is a lack of sufficient mathematicalanalysis and control design tools for flow controlproblems. This includes mathematical models that areamenable to control design. The research presented inthis book makes an effort at closing this gap by 1)presenting a reduced-order modeling method utilizinga novel technique for input separation on ProperOrthogonal Decomposition (POD)/Galerkin Projection(GP) based models, 2) introducing a technique basedon averaging theory and center manifold theory so asto reveal certain structures embedded in the model,and 3) developing nonlinear analysis and controldesign approaches for the resulting model. The theoryis complemented by examples and case studies asappropriate, including the case of cavity flow control. N° de réf. du vendeur 9783639100518
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Taschenbuch. Etat : Neu. New Directions in Flow Control | Reduced Order Modeling, Nonlinear Analysis and Control Design Methods for the Control of Fluid Flow Problems | Co ku Kasnako lu | Taschenbuch | Kartoniert / Broschiert | Englisch | 2008 | VDM Verlag Dr. Müller | EAN 9783639100518 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu. N° de réf. du vendeur 101682071
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