9783319821405 - machine learning control – taming nonlinear dynamics and turbulence (fluid mechanics and its applications, 116, band 116) von duriez, thomas; brunton, steven l.; noack, bernd r. (2 Ergebnisse)
Sprache: Englisch
Verlag: Springer, 2018
Serie: Fluid Mechanics and Its Applications, Buch 113 von 136. Buch 113 von 136 - Fluid Mechanics and Its Applications
- Softcover
Anbieter: preigu, Osnabrück, Deutschlandpreigu
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EUR 86,30
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Taschenbuch. Zustand: Neu. Machine Learning Control - Taming Nonlinear Dynamics and Turbulence | Thomas Duriez (u. a.) | Taschenbuch | Fluid Mechanics and Its Applications | xx | Englisch | 2018 | Springer | EAN 9783319821405 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[…dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer International Publishing, 2018
Serie: Fluid Mechanics and Its Applications, Buch 113 von 136. Buch 113 von 136 - Fluid Mechanics and Its Applications
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 96,29
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This is the first textbookon a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning c…ontrol (MLC) is motivated and detailed in Chapters 1 and 2. In Chapter 3, methods of linear control theory are reviewed. In Chapter 4, MLC is shown to reproduce known optimal control laws for linear dynamics (LQR, LQG). In Chapter 5, MLC detects and exploits a strongly nonlinear actuation mechanism of a low-dimensional dynamical system when linear control methods are shown to fail. Experimental control demonstrations from a laminar shear-layer to turbulent boundary-layers are reviewed in Chapter 6, followed by general good practices for experiments in Chapter 7. The book concludes with an outlook on the vast futureapplications of MLC in Chapter 8. Matlab codes are providedfor easy reproducibility of the presented results. The book includesinterviews with leading researchers in turbulence control (S. Bagheri, B. Batten, M. Glauser, D. Williams) and machine learning (M. Schoenauer) for a broader perspective. All chapters have exercises and supplemental videos will be available through YouTube.
