This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. The key concept for the gain design is to balance multiple performance indices such as high tracking precision, effective noise reduction, and fast convergence speed. These gain design techniques can be applied to various control algorithms for stochastic systems to realize a high tracking performance. This book provides a series of design and analysis techniques for the establishment of a systematic framework of gain design in SILC. The book is intended for scholars and graduate students who are interested in stochastic control, recursive algorithms design, and iterative learning control.
"Sinopsis" puede pertenecer a otra edición de este libro.
Dong Shen received the B.S. degree in mathematics from the School of Mathematics, Shandong University, Jinan, China, in 2005, and the Ph.D. degree in mathematics from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences (CAS), Beijing, China, in 2010. From 2010 to 2012, he was a postdoctoral fellow with the Institute of Automation, CAS. From 2012 to 2019, he was with the College of Information Science and Technology, Beijing University of Chemical Technology, Beijing. In 2016 and 2019, he was a visiting scholar with the National University of Singapore, Singapore, and RMIT University, Melbourne, VIC, Australia, respectively. Since 2020, he has been a professor at the School of Mathematics, Renmin University of China, Beijing. His research interests include iterative learning control, stochastic optimization, stochastic systems, and distributed artificial intelligence.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Paperback. Condición: new. Paperback. This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. The key concept for the gain design is to balance multiple performance indices such as high tracking precision, effective noise reduction, and fast convergence speed. These gain design techniques can be applied to various control algorithms for stochastic systems to realize a high tracking performance. This book provides a series of design and analysis techniques for the establishment of a systematic framework of gain design in SILC. The book is intended for scholars and graduate students who are interested in stochastic control, recursive algorithms design, and iterative learning control. This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9789819782833
Cantidad disponible: 1 disponibles
Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. Paperback. This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. The key concept for the gain design is to balance multiple performance indices such as high tracking precision, effective noise reduction, and fast convergence speed. These gain design techniques can be applied to various control algorithms for stochastic systems to realize a high tracking performance. This book provides a series of design and analysis techniques for the establishment of a systematic framework of gain design in SILC. The book is intended for scholars and graduate students who are interested in stochastic control, recursive algorithms design, and iterative learning control. This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9789819782833
Cantidad disponible: 1 disponibles
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. The key concept for the gain design is to balance multiple performance indices such as high tracking precision, effective noise reduction, and fast convergence speed. These gain design techniques can be applied to various control algorithms for stochastic systems to realize a high tracking performance. This book provides a series of design and analysis techniques for the establishment of a systematic framework of gain design in SILC. The book is intended for scholars and graduate students who are interested in stochastic control, recursive algorithms design, and iterative learning control. 350 pp. Englisch. Nº de ref. del artículo: 9789819782833
Cantidad disponible: 2 disponibles
Librería: moluna, Greven, Alemania
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Nº de ref. del artículo: 2856877446
Cantidad disponible: Más de 20 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. The key concept for the gain design is to balance multiple performance indices such as high tracking precision, effective noise reduction, and fast convergence speed. These gain design techniques can be applied to various control algorithms for stochastic systems to realize a high tracking performance. This book provides a series of design and analysis techniques for the establishment of a systematic framework of gain design in SILC. The book is intended for scholars and graduate students who are interested in stochastic control, recursive algorithms design, and iterative learning control. Nº de ref. del artículo: 9789819782833
Cantidad disponible: 1 disponibles
Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Variable Gain Design in Stochastic Iterative Learning Control | Dong Shen | Taschenbuch | Intelligent Control and Learning Systems | xi | Englisch | 2026 | Springer | EAN 9789819782833 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Nº de ref. del artículo: 134487531
Cantidad disponible: 5 disponibles
Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. Nº de ref. del artículo: 26405507670
Cantidad disponible: 4 disponibles
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. The key concept for the gain design is to balance multiple performance indices such as high tracking precision, effective noise reduction, and fast convergence speed. These gain design techniques can be applied to various control algorithms for stochastic systems to realize a high tracking performance. This book provides a series of design and analysis techniques for the establishment of a systematic framework of gain design in SILC. The book is intended for scholars and graduate students who are interested in stochastic control, recursive algorithms design, and iterative learning control.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 364 pp. Englisch. Nº de ref. del artículo: 9789819782833
Cantidad disponible: 1 disponibles
Librería: Majestic Books, Hounslow, Reino Unido
Condición: New. Print on Demand. Nº de ref. del artículo: 408695177
Cantidad disponible: 4 disponibles
Librería: Biblios, Frankfurt am main, HESSE, Alemania
Condición: New. PRINT ON DEMAND. Nº de ref. del artículo: 18405507676
Cantidad disponible: 4 disponibles