Articoli correlati a Stochastic Lagrangian Adaptation
Sinossi
This book introduces a cutting-edge continuous time stochastic linear quadratic (LQ) adaptive control algorithm for fully observed linear stochastic systems with unknown parameters. The adaptive estimation algorithm is engineered to drive the maximum likelihood estimate into the set of parameters representing the true closed-loop dynamics. By incorporating a performance monitoring feature, this approach ensures that the estimate converges to the true system parameters. Concurrently, it delivers optimal long-term LQ closed-loop performance. This groundbreaking work offers a significant advancement in the field of stochastic control systems.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull?autore
Peter E. Caines received the BA in mathematics from Oxford University in 1967 and the PhD in systems and control theory in 1970 from Imperial College, University of London, supervised by David Q. Mayne, FRS. Following PDF and visiting positions,a he joined McGill University in 1980, where he is Distinguished James McGill Professor and Macdonald Chair in the Department of Electrical and Computer Engineering. He received the IEEE Control Systems Society Bode Lecture Prize (2009), is a Fellow of IFAC, CIFAR, SIAM, IEEE, the IMA (UK) and the Royal Society of Canada (2003), and is a member of Professional Engineers Ontario. His monograph, Linear Stochastic Systems (Wiley, 1988), is now published as a SIAM Classic and his research interests include stochastic and hybrid systems, and mean field (control and games) systems on large networks.
David Levanony (BSc., Aerospace Eng., 1985, MSc., Aerospace Eng., 1988, DSc., Electrical Eng., 1992, Technion, Haifa, Israel) is a Senior Lecturer with the School of Electrical and Computer Engineering, Ben Gurion University, Beer Sheva, Israel and a consultant with the defense industry in Israel.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreSpringer-Verlag GmbH
- Data di pubblicazione2024
- ISBN 10 3031737571
- ISBN 13 9783031737572
- RilegaturaCopertina flessibile
- LinguaInglese
- Numero di pagine84
- Contatto del produttorenon disponibile
Compra nuovo
Visualizza questo articolo
EUR 44,31
EUR 9,70 per la spedizione da Germania a Italia
Destinazione, tempi e costiRisultati della ricerca per Stochastic Lagrangian Adaptation
Foto dell'editore
Stochastic Lagrangian Adaptation (SpringerBriefs in Mathematics)
Da: Books From California, Simi Valley, CA, U.S.A.
Valutazione del venditore 4 su 5 stelle
paperback. Condizione: Fine. Codice articolo mon0003657560
Quantità: 1 disponibili
Foto dell'editore
Stochastic Lagrangian Adaptation (SpringerBriefs in Mathematics)
Da: Books From California, Simi Valley, CA, U.S.A.
Valutazione del venditore 4 su 5 stelle
paperback. Condizione: Good. Codice articolo mon0003660149
Quantità: 2 disponibili
Foto dell'editore
Stochastic Lagrangian Adaptation (SpringerBriefs in Mathematics)
Da: Books From California, Simi Valley, CA, U.S.A.
Valutazione del venditore 4 su 5 stelle
paperback. Condizione: Very Good. Codice articolo mon0003658050
Quantità: 3 disponibili
Immagini fornite dal venditore
Stochastic Lagrangian Adaptation
Print on DemandDa: moluna, Greven, Germania
Valutazione del venditore 4 su 5 stelle
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Codice articolo 1829341750
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Stochastic Lagrangian Adaptation
Editore:
Springer, Berlin, Springer Nature Switzerland, Springer, 2024
ISBN 10: 3031737571
ISBN 13: 9783031737572
Nuovo
Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces a cutting-edge continuous time stochastic linear quadratic (LQ) adaptive control algorithm for fully observed linear stochastic systems with unknown parameters. The adaptive estimation algorithm is engineered to drive the maximum likelihood estimate into the set of parameters representing the true closed-loop dynamics. By incorporating a performance monitoring feature, this approach ensures that the estimate converges to the true system parameters. Concurrently, it delivers optimal long-term LQ closed-loop performance. This groundbreaking work offers a significant advancement in the field of stochastic control systems. 77 pp. Englisch. Codice articolo 9783031737572
Quantità: 2 disponibili
Immagini fornite dal venditore
Stochastic Lagrangian Adaptation
ISBN 10: 3031737571
ISBN 13: 9783031737572
Nuovo
Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces a cutting-edge continuous time stochastic linear quadratic (LQ) adaptive control algorithm for fully observed linear stochastic systems with unknown parameters. The adaptive estimation algorithm is engineered to drive the maximum likelihood estimate into the set of parameters representing the true closed-loop dynamics. By incorporating a performance monitoring feature, this approach ensures that the estimate converges to the true system parameters. Concurrently, it delivers optimal long-term LQ closed-loop performance. This groundbreaking work offers a significant advancement in the field of stochastic control systems. Codice articolo 9783031737572
Quantità: 1 disponibili
Immagini fornite dal venditore
Stochastic Lagrangian Adaptation
ISBN 10: 3031737571
ISBN 13: 9783031737572
Nuovo
Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Neuware -This book introduces a cutting-edge continuous time stochastic linear quadratic (LQ) adaptive control algorithm for fully observed linear stochastic systems with unknown parameters. The adaptive estimation algorithm is engineered to drive the maximum likelihood estimate into the set of parameters representing the true closed-loop dynamics. By incorporating a performance monitoring feature, this approach ensures that the estimate converges to the true system parameters. Concurrently, it delivers optimal long-term LQ closed-loop performance. This groundbreaking work offers a significant advancement in the field of stochastic control systems.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 84 pp. Englisch. Codice articolo 9783031737572
Quantità: 2 disponibili
Foto dell'editore
Stochastic Lagrangian Adaptation (SpringerBriefs in Mathematics)
Da: California Books, Miami, FL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. Codice articolo I-9783031737572
Quantità: Più di 20 disponibili
Foto dell'editore
Stochastic Lagrangian Adaptation (SpringerBriefs in Mathematics)
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. In. Codice articolo ria9783031737572_new
Quantità: Più di 20 disponibili
Foto dell'editore
Stochastic Lagrangian Adaptation
Da: Revaluation Books, Exeter, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: Brand New. 83 pages. 9.25x6.10x9.21 inches. In Stock. Codice articolo x-3031737571
Quantità: 2 disponibili