Verlag: Springer Nature Singapore, 2017
ISBN 10: 9811040796 ISBN 13: 9789811040795
Sprache: Englisch
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In den WarenkorbZustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.
Verlag: Springer Nature Singapore, 2017
ISBN 10: 9811040796 ISBN 13: 9789811040795
Sprache: Englisch
Anbieter: Buchpark, Trebbin, Deutschland
EUR 83,09
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In den WarenkorbZustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher.
Verlag: Springer Nature Singapore, 2019
ISBN 10: 9811350434 ISBN 13: 9789811350436
Sprache: Englisch
Anbieter: Buchpark, Trebbin, Deutschland
EUR 83,72
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In den WarenkorbZustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.
Verlag: Springer Nature Singapore, Springer Nature Singapore Jan 2019, 2019
ISBN 10: 9811350434 ISBN 13: 9789811350436
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum.With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 252 pp. Englisch.
Verlag: Springer Nature Singapore, Springer Nature Singapore Jun 2017, 2017
ISBN 10: 9811040796 ISBN 13: 9789811040795
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
EUR 149,79
Währung umrechnenAnzahl: 2 verfügbar
In den WarenkorbBuch. Zustand: Neu. Neuware -This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum.With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 252 pp. Englisch.
Verlag: Springer Nature Singapore, Springer Nature Singapore, 2019
ISBN 10: 9811350434 ISBN 13: 9789811350436
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum.With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 151,67
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In den WarenkorbZustand: New. In.
Verlag: Springer Nature Singapore, Springer Nature Singapore, 2017
ISBN 10: 9811040796 ISBN 13: 9789811040795
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 153,90
Währung umrechnenAnzahl: 1 verfügbar
In den WarenkorbBuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system model; when the system model is not known, adaptive dynamic programming is implemented according to the system data, effectively making the performance of the system converge to the optimum.With various real-world examples to complement and substantiate the mathematical analysis, the book is a valuable guide for engineers, researchers, and students in control science and engineering.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 216,24
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In den WarenkorbPaperback. Zustand: Brand New. reprint edition. 252 pages. 9.25x6.10x0.67 inches. In Stock.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbHardcover. Zustand: Brand New. 230 pages. 9.25x6.25x0.75 inches. In Stock.