Emergent Behavior Detection and Task Coordination for Multiagent Systems | A Distributed Estimation and Control Approach
Langue : anglais
Edité par Springer, 2022
Série : Livre 350 sur 378 - Studies in Systems, Decision and Control
- Livre broché
- Neuf
Vendeur : preigu, Osnabrück, Allemagnepreigu
Vendeur AbeBooks depuis 5 août 2024
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Emergent Behavior Detection and Task Coordination for Multiagent Systems | A Distributed Estimation and Control Approach | Jing Wang | Taschenbuch | Studies in Systems, Decision and Control | xx | Englisch | 2022 | Springer | EAN 9783030868956 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
N° de réf. du vendeur 125330345
- Titre
- Emergent Behavior Detection and Task Coordination for Multiagent Systems | A Distributed Estimation and Control Approach
- Auteur
- Jing Wang
- Éditeur
- Springer
- Année de publication
- 2022
- État de l'article
- Neu
- Reliure
- Taschenbuch
- Langue
- anglais
- ISBN à 10 chiffres
- 3030868958
- ISBN à 13 chiffres
- 9783030868956
- Poids de l'article
- 394 grammes
- Dimensions
- 235 x 155 x 15 mm
- Série
- Livre 350 sur 378: Studies in Systems, Decision and Control
- Catalogues du vendeur
- Bücher
This book addresses problems in the modeling, detection, and control of emergent behaviors and task coordination in multiagent systems. It presents a unified solution to such problems in terms of distributed estimation, distributed control, and optimization of interaction topologies and dynamics.
Four aspects of the technical solutions in the book are presented: First, the impact of interaction dynamics on the convergence conditions related to interaction topologies is discussed, utilizing a discontinuous cooperative control algorithm of updated design. Second, distributed least-squares and Kalman filtering algorithms for agents with limited interactions are elaborated upon. Third, a general framework of distributed nonlinear control is established, and distributed adaptive control for nonlinear systems with more general uncertainties is presented. Based on the proposed framework, a distributed nonlinear controller is designed to deal with task coordination of robotic systems with nonholonomic constraints. Finally, the problem of optimal multiagent task coordination is addressed and solutions based on approximate dynamic programming and approximate distributed gradient estimation are presented.Emergent Behavior Detection and Task Coordination for Multiagent Systems is of interest to practicing engineers in areas such as robotics and cyber-physical systems, researchers in the field of systems, controls, and robotics, and senior undergraduate and graduate students.
« Synopsis » peut appartenir à une autre édition de cet ouvrage.
À propos de l’auteur
Dr Jing Wang received his Ph.D. in control theory and control engineering in 1997 from Central South University, China. He was a Postdoctoral Research Fellow at the Institute of Computing Technology, Chinese Academy of Sciences, from 1997 to 1999 and at the Department of Electrical & Computer Engineering, National University of Singapore, from 1999 to 2002. From 2002 to 2007, he worked at the School of Electrical Engineering and Computer Science of the University of Central Florida as a Research Assistant Professor. From 2007 to 2014, he was with the Department of Computer Engineering & Computer Science, Bethune-Cookman University, Florida. Since August 2014, he has been working at the Department of Electrical and Computer Engineering, Bradley University, Illinois, and is currently an Associate Professor. He has published over 130 papers in peer-reviewed international journals and conferences and 4 book chapters, mainly in the areas of nonlinear control, cooperative control, adaptive control, robotics, and optimization. His research has been supported by governmental agencies (NSF, AFRL, AFOSR, NASA, DOT) and industry. Dr Wang is a Senior Member of the IEEE. His current research interests include cooperative control and robotics, distributed optimization and learning, nonlinear systems and control theory, and control applications in power converters and smart grids
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