Collective Behavior in Complex Networked Systems under Imperfect Communication
(Sprache: Englisch)
This book aims to explain how collective behavior is formed via local interactions under imperfect communication in complex networked systems. It also presents some new distributed protocols or algorithms for complex networked systems to comply with...
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This book aims to explain how collective behavior is formed via local interactions under imperfect communication in complex networked systems. It also presents some new distributed protocols or algorithms for complex networked systems to comply with bandwidth limitation and tolerate communication delays.This book will be of particular interest to the readers due to the benefits: 1) it studies the effect of time delay and quantization on the collective behavior by non-smooth analytical technique and algebraic graph theory; 2) it introduces the event-based consensus method under delayed information transmission; In the meantime, it presents some novel approaches to handle the communication constraints in networked systems; 3) it gives some synchronization and control strategies for complex networked systems with limited communication abilities. Furthermore, it provides a consensus recovery approach for multi-agent systems with node failure. Also, it presentsinteresting results about bipartite consensus and fixed-time/finite-time bipartite consensus of networks with cooperative and antagonistic interactions.
Inhaltsverzeichnis zu „Collective Behavior in Complex Networked Systems under Imperfect Communication “
Introduction.- Consensus over Directed Static Networks with Arbitrary Finite Communication Delays.- Practical Consensus of Multi-agent Networks.- Multi-agent Consensus with Quantization and Communication Delays.- Event-based Network Consensus with Communication Delays.- Consensus of Networked Multi-agent Systems with Antagonistic Interactions and Communication Delays.- Finite-time and Fixed-time Bipartite Consensus for Multi-agent Systems with Antagonistic Interactions.- Globally Exponential Synchronization and Synchronizability for General Dynamical Networks.- Pinning Cluster Synchronization in an Array of Coupled Neural Networks under Event-based Mechanism.- Multi-agent Consensus Recovery Approach under Node Failure.- Conclusion and Future WorkAutoren-Porträt von Jianquan Lu, Lulu Li, Daniel W.C. Ho, Jinde Cao
Jianquan Lu received the B.S. degree in mathematics from Zhejiang Normal University, Zhejiang, China, in 2003, the M.S. degree in mathematics from Southeast University, Nanjing, China, in 2006, and the Ph.D. degree in applied mathematics from City University of Hong Kong, Hong Kong, in 2009. From 2010 to 2012, he was an Alexander von Humboldt Research Fellow in PIK, Germany. He is currently a professor at the Department of Systems Science, School of Mathematics, Southeast University, Nanjing, China. His current research interests include collective behavior in complex dynamical networks and multi-agent systems, Boolean networks, and hybrid systems. He has published over 100 papers in refereed international journals.Bibliographische Angaben
- Autoren: Jianquan Lu , Lulu Li , Daniel W.C. Ho , Jinde Cao
- 2022, 1st ed. 2021, XIV, 269 Seiten, 54 farbige Abbildungen, Masse: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 981161508X
- ISBN-13: 9789811615085
Sprache:
Englisch
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