内容简介：　　　

　　Synchronization, consensus and flocking are ubiquitous requirements in networked systems. Pinning Control of Complex Networked Systems investigates these requirements by using the pinning control strategy, which aims to control the whole dynamical network with huge numbers of nodes by imposing controllers for only a fraction of the nodes. As the direct control of every node in a dynamical network with huge numbers of nodes might be impossible or unnecessary, it’s then very important to use the pinning control strategy for the synchronization of complex dynamical networks. The research on pinning control strategy in consensus and flocking of multi-agent systems can not only help us to better understand the mechanisms of natural collective phenomena, but also benefit applications in mobile sensor/robot networks. This book offers a valuable resource for researchers and engineers working in the fields of control theory and control engineering.

英文目录：

1 Overview
　　1.1 Introduction
　　1.2 Synchronization of Complex Dynamical Networks via Pinning
　　　　1.2.1 Stability Conditions for Complete Synchronization
　　　　1.2.2 Stability Conditions for Cluster Synchronization
　　　　1.2.3 Selective Strategies of Pinning Control
　　　　1.2.4 Controllable Regions
　　　　1.2.5 Control Methodologies
　　1.3 Consensus and Flocking of Multi-Agent Systems via Pinning
　　　　1.3.1 Single Virtual Leader Case
　　　　1.3.2 Multiple Virtual Leaders Case
　　　　1.3.3 Connectivity Maintenance
　　1.4 Conclusions and Notes
　　References
2 Pinning Control for Complete Synchronization of Complex Dynamical Networks
　　2.1 Complex Network Models
　　　　2.1.1 ER Random Network Model
　　　　2.1.2 BA Scale-Free Network Model
　　　　2.1.3 A Directed Scale-Free Network Model
　　2.2 Stability Conditions for Complete Synchronization of Complex Dynamical Networks
　　　　2.2.1 Global Stability Conditions
　　　　2.2.2 Local Stability Conditions
　　2.3 Virtual Control of Pinned Complex Dynamical Networks
　　2.4 Selective Strategies of Pinning Control
　　　　2.4.1 Pinning Control Based on Node-Degree
　　　　2.4.2 Pinning Control Based on Control Rank
　　2.5 Conclusions and Notes
　　References
3 Pinning Control for Cluster Synchronization of Complex Dynamical Networks
　　3.1 Problem Statement
　　3.2 Decentralized Adaptive Pinning Control Scheme
　　　　3.2.1 Algorithm Description
　　　　3.2.2 Main Results and Theoretical Analysis
　　　　3.2.3 Complete Synchronization Case
　　3.3 Simulation Study
　　　　3.3.1 Example 1: Three Clusters
　　　　3.3.2 Example 2: One Cluster
　　3.4 Conclusions and Notes
　　References
4 Distributed Pinning-Controlled Second-Order Consensus of Multi-Agent Systems
　　4.1 Consensus Without Connectivity Assumptions
　　　　4.1.1 Problem Statement
　　　　4.1.2 Consensus Without a Leader
　　　　4.1.3 Consensus with a Leader
　　　　4.1.4 Simulation Study
　　4.2 Consensus with Preserved Network Connectivity
　　　　4.2.1 Problem Statement
　　　　4.2.2 Algorithm Design and Main Results
　　　　4.2.3 Consensus with a Virtual Leader
　　　　4.2.4 Simulation Study
　　4.3 Adaptive Consensus of Networked Mobile Agents with Nonlinear Dynamics
　　　　4.3.1 Problem Statement
　　　　4.3.2 Main Results
　　　　4.3.3 Simulation Study
　　4.4 Conclusions and Notes
　　References
5 Distributed Pinning-Controlled Consensus in a Heterogeneous Influence Network
　　5.1 Backgrounds and Problem Statement
　　5.2 Consensus in a Heterogeneous Influence Network
　　5.3 Pinning Controlled Consensus in a Heterogeneous Influence Network
　　5.4 Conclusions and Notes
　　References
6 Distributed Pinning-Controlled Flocking with a Virtual Leader
　　6.1 Introduction
　　6.2 Backgrounds and Problem Statement
　　6.3 Flocking with a Fraction of Informed Agents
　　　　6.3.1 Algorithm Description and Main Results
　　　　6.3.2 Cohesive Analysis
　　　　6.3.3 Velocity Matching Analysis
　　　　6.3.4 Collision Avoidance Analysis
　　6.4 Flocking with a Virtual Leader of Varying Velocity
　　　　6.4.1 Algorithm Description and Main Result
　　　　6.4.2 Theoretical Analysis
　　6.5 Simulation Study
　　　　6.5.1 Flocking with a Fraction of Informed Agents
　　　　6.5.2 Flocking with a Virtual Leader of Varying Velocity
　　　　6.5.3 Flocking with a Fraction of Informed Agents and a Virtual Leader of Varying Velocity
　　6.6 Conclusions and Notes
　　References
7 Distributed Pinning-Controlled Flocking with Preserved Network Connectivity
　　7.1 Flocking Based only on Position Measurements
　　　　7.1.1 Background and Problem Statement
　　　　7.1.2 Fundamental Flocking Algorithm
　　　　7.1.3 Flocking with a Virtual Leader
　　　　7.1.4 Simulation Study
　　7.2 Adaptive Flocking of Multiple Agents Governed by Nonlinear Dynamics
　　　　7.2.1 Preliminaries and Problem Statement
　　　　7.2.2 Main Results
　　　　7.2.3 Simulation Study
　　7.3 Conclusions and Notes
References
Index