Description

Book Synopsis
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 presents interesting results about bipartite consensus and fixed-time/finite-time bipartite consensus of networks with cooperative and antagonistic interactions.




Table of Contents

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 Work


Collective Behavior in Complex Networked Systems under Imperfect Communication

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    Order before 4pm tomorrow for delivery by Wed 10 Jun 2026.

    A Hardback by Jianquan Lu, Lulu Li, Daniel W.C. Ho

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      View other formats and editions of Collective Behavior in Complex Networked Systems under Imperfect Communication by Jianquan Lu

      Publisher: Springer Verlag, Singapore
      Publication Date: 07/07/2021
      ISBN13: 9789811615054, 978-9811615054
      ISBN10:

      Description

      Book Synopsis
      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 presents interesting results about bipartite consensus and fixed-time/finite-time bipartite consensus of networks with cooperative and antagonistic interactions.




      Table of Contents

      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 Work


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