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Thisbookaimstoexplainhowcollectivebehaviorisformedvialocalinteractionsunderimperfectcommunicationincomplexnetworkedsystems.Italsopresentssomenewdistributedprotocolsoralgorithmsforcomplexnetworkedsystemstocomplywithbandwidthlimitationandtoleratecommunicationdelays.《BR》 Thisbookwillbeofparticularinteresttothereadersduetothebenefits:1)itstudiestheeffectoftimedelayandquantizationonthecollectivebehaviorbynon-smoothanalyticaltechniqueandalgebraicgraphtheory;2)itintroducestheevent-basedconsensusmethodunderdelayedinformationtransmission;Inthemeantime，itpresentssomenovelapproachestohandlethecommunicationconstraintsinnetworkedsystems;3)itgivessomesynchronizationandcontrolstrategiesforcomplexnetworkedsystemswithlimitedcommunicationabilities.Furthermore，itprovidesaconsensusrecoveryapproachformulti-agentsystemswithnodefailure.Also，itpresentsinterestingresultsaboutbipartiteconsensusandfixed-time/finite-timebipartiteconsensusofnetworkswithcooperativeandantagonisticinteractions.
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Contents Preface List of Symbols Chapter 1 Introduction 1 1.1 Background 1 1.2 Research problems 3 1.2.1 Consensus and practical consensus 6 1.2.2 General model description 6 1.3 Mathematical preliminaries 8 1.3.1 Matrices and graphs 8 1.3.2 Signed graphs 9 1.3.3 Quantizer 11 1.3.4 Discontinuous differential equations 12 1.3.5 Some lemmas 13References 14 Chapter 2 Consensus over Directed Static Networks with Arbitrary Finite Communication Delays 20 2.1 Linear coupling 21 2.1.1 The case of leaderless 212.1.2 The case with one well-informed leader 23 2.2 Nonlinear coupling 25 2.3 Hierarchical structure 272.4 Numerical examples 28 2.5 Summary 32 References 32 Chapter 3 Practical Consensus of Multi-Agent Networks with Communication Constraints 35 3.1 Practical consensus with quantized data 36 3.1.1 Model description 36 3.1.2 Finite-time practical consensus under quantization 37 3.1.3 Numerical example 41 3.2 Consensus with hybrid communication constraints 42 3.2.1 Model description and preliminaries 42 3.2.2 The existence of the Filippov solution 43 3.2.3 Practical consensus under quantization and time delay 46 3.2.4 Numerical example 59 3.2.5 Discussions 613.3 Summary 64 References 65 Chapter 4 Multi-Agent Consensus with Quantization and Communication Delays 67 4.1 Discrete-time case 674.1.1 Model description 68 4.1.2 Main results 684.1.3 Numerical example 73 4.2 Continuous-time case 744.2.1 Model description and preliminaries 74 4.2.2 The existence of the Filippov solution 75 4.2.3 Consensus analysis under quantization and time delays 77 4.2.4 Numerical example 86 4.3 Summary 87 References 87 Chapter 5 Event-Based Network Consensus with Communication Delays 89 5.1 Distributed discrete-time event-triggered consensus with delays 89 5.1.1 Model description 90 5.1.2 Distributed event-triggered approach 91 5.1.3 Numerical example 97 5.2 Distributed continuous-time event-triggered consensus with delays 99 5.2.1 Model description 99 5.2.2 Asynchronously distributed event-triggered approach 100 5.2.3 Synchronously event-triggered control 107 5.2.4 Numerical example 110 5.3 Summary 111 References 112 Chapter 6 Consensus of Networked Multi-Agent Systems with Antagonistic Interactions and Communication Delays 114 6.1 Continuous-time multi-agent consensus 115 6.1.1 Linear coupling 115 6.1.2 Nonlinear coupling 121 6.1.3 Numerical examples 124 6.2 Discrete-time multi-agent consensus 127 6.2.1 Distributed event-based bipartite consensus 127 6.2.2 Self-triggered approach 140 6.2.3 Numerical example 143 6.3 Summary 146 References 146 Chapter 7 Finite-Time and Fixed-Time Bipartite Consensus for Multi-Agent Systems with Antagonistic Interactions 148 7.1 Preliminaries 150 7.2 Finite-time bipartite consensus 151 7.2.1 Finite-time bipartite consensus protocol 151 7.2.2 Pinning bipartite consensus protocol 156 7.2.3 Numerical examples 159 7.3 Fixed-time bipartite consensus 163 7.3.1 General fixed-time bipartite consensus 165 7.3.2 Signed-average fixed-time bipartite consensus 168 7.3.3 Numerical examples 171 7.4 Summary 173 References 174 Chapter 8 Globally Exponential Synchronization and Synchronizability for General Dynamical Networks 178 8.1 Preliminaries 1798.2 Synchronization analysis 181 8.2.1 Irreducible case 181 8.2.2 Reducible case 1898.3 Numerical examples 193 8.4 Summary 200 References 200 Chapter 9 Pinning Cluster Synchronization in an Arrayof Coupled Neural Networks under Event-Based Mechanism 203 9.1 Preliminaries and problem formulation 204 9.2 Pinning cluster synchronization under event-triggered mechanism 207 9.3 Pinning cluster synchronization under self-triggered mechanism 214 9.4 Numerical example 217 9.5 Summary 222 References 222 Chapter 10 Multi-Agent Consensus Recovery Approach under Node Failure 225 10.1 Preliminaries 22510.2 Consensus analysis of general multi-agent networks 227 10.3 Consensus recovery approach 232 10.4 Numerical examples 239 10.5 Summary 244 References 244 Chapter 11 Conclusion and FutureWork 246 11.1 Conclusion 24611.2 Future work 247Color Illustrations
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