Data-driven Optimization and Control for Autonomous Energy Systems

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Éditeur :

Springer

Paru le : 2025-10-19

This book introduces a pioneering framework for monitoring and controlling autonomous energy systems, distinguished by its use of physics-informed deep neural networks. These networks provide accurate estimations and forecasts, interlacing with advanced composite optimization algorithms to simplify ...
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Éditeur

Collection
n.c

Parution
2025-10-19

Pages
156 pages

EAN papier
9789819517817

Auteur(s) du livre


Gang Wang received a B.Eng. degree in automatic control and a Ph.D. degree in control science and engineering from the Beijing Institute of Technology, Beijing, China, and a Ph.D. degree in electrical and computer engineering from the University of Minnesota, Minneapolis, MN, USA. He is currently Professor with the School of Automation, Beijing Institute of Technology. Jian Sun received his B.Sc. degree from the Department of Automation and Electric Engineering, Jilin Institute of Technology, Changchun, China, the M.Sc. degree from the Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences (CAS), Changchun, China, and the Ph.D. degree from the Institute of Automation, CAS, Beijing, China. He is currently Professor with the School of Automation, Beijing Institute of Technology. Jie Chen received his B.Sc., M.Sc., and the Ph.D. degrees in Control Theory and Control Engineering from the Beijing Institute of Technology, Beijing, China. He is currently Professor with the School of Automation, Beijing Institute of Technology and Director of the National Key Laboratory of Autonomous Intelligent Unmanned Systems (KAIUS).

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EAN PDF
9789819517824
Prix
168,79 €
Nombre pages copiables
1
Nombre pages imprimables
15
Taille du fichier
14162 Ko
EAN EPUB
9789819517824
Prix
168,79 €
Nombre pages copiables
1
Nombre pages imprimables
15
Taille du fichier
26235 Ko

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