Distributed Cooperative Control of Multi-agent Systems
Inbunden, Engelska, 2016
1 959 kr
Produktinformation
- Utgivningsdatum2016-11-11
- Mått163 x 246 x 18 mm
- Vikt544 g
- FormatInbunden
- SpråkEngelska
- Antal sidor350
- FörlagJohn Wiley & Sons Inc
- ISBN9781119246206
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Wenwu Yu, Southeast University, China, received his Ph.D. degree from the Department of Electronic Engineering, City University of Hong Kong, in 2010 and is currently a full Professor in the Research Center for Complex Systems and Network Sciences. He is the author or coauthor of about 100 refereed international journal and conference papers with more than 3400 citations, and a reviewer of several journals. His research interests include multi-agent systems, nonlinear dynamics and control, complex networks and systems, neural networks, cryptography, and communications.Guanghui Wen, Southeast University, China,received the Ph.D. degree in mechanical systems and control from Peking University, China, in 2012. From September 2012 to January 2013, he was a Research Associate and Post-Doctor in the University of New South Wales at Australian Defence Force Academy, Australia. Currently, he is a Lecturer in the Department of Mathematics, Southeast University, China. His research focuses on cooperative control of multi-agent systems and cyber-physical systems.Guanrong Chen, City University of Hong Kong, China, has been a chair professor and the founding director of the Centre for Chaos and Complex Networks at City University of Hong Kong since year 2000, prior to which he was a tenured full professor at the University of Houston, Texas, USA. Prof. Chen was elected Member of the Academia Europaea in 2014. In the past, he was elected IEEE Fellow in 1997, and was conferred Honorary Doctorates by Saint Petersburg State University of Russia in 2011 and by University of Le Havre of France in 2014. Other honours include the 2011 Euler Gold Medalist and the 2008 and 2012 Chinese State Natural Science Awards as well as 5 best journal paper awards. He is Honorary Professor at different ranks in some 30 universities worldwide. Prof. Chen's main research pursuit is in nonlinear systems, control and dynamics, as well as complex networks. He currently is the Editor-in-Chief for the International Journal of Bifurcation and Chaos.Jinde Cao, Southeast University, China,received the B.S. degree from Anhui Normal University, Wuhu, China, the M.S. degree from Yunnan University, Kunming, China, and the Ph.D. degree from Sichuan University, Chengdu, China, all in mathematics/applied mathematics, in 1986, 1989, and 1998, respectively. He is currently a TePin Professor and Doctoral Advisor at the Southeast University. Prior to this, he was a Professor at Yunnan University from 1996 to 2000. He is the author or coauthor of more than 160 journal papers and five edited books and a reviewer of Mathematical Reviews and ZentralblattMath. His research interests include nonlinear systems, neural networks, complex systems and complex networks, stability theory, and applied mathematics. Professor Cao is an Associate Editor of the IEEE Transactions on Cybernetics, Journal of the Franklin Institute, Neural Networks.
- Preface ix1 Introduction 11.1 Background 11.1.1 Networked Multi-agent Systems 11.1.2 Collective Behaviors and Cooperative Control in Multi-agent Systems 21.1.3 Network Control in Multi-agent Systems 41.1.4 Distributed Consensus Filtering in Sensor Networks 51.2 Organization 62 Consensus in Multi-agent Systems 112.1 Consensus in Linear Multi-agent Systems 112.1.1 Preliminaries 112.1.2 Model Formulation and Results 132.2 Consensus in Nonlinear Multi-agent Systems 152.2.1 Preliminaries and Model Formulation 152.2.2 Local Consensus of Multi-agent Systems 162.2.3 Global Consensus of Multi-agent Systems in General Networks 192.2.4 Global Consensus of Multi-agent Systems in Virtual Networks 262.2.5 Simulation Examples 292.3 Notes 303 Second-Order Consensus in Multi-agent Systems 313.1 Second-Order Consensus in Linear Multi-agent Systems 323.1.1 Model Formulation 323.1.2 Second-Order Consensus in Directed Networks 333.1.3 Second-Order Consensus in Delayed Directed Networks 373.1.4 Simulation Examples 413.2 Second-Order Consensus in Nonlinear Multi-agent Systems 423.2.1 Preliminaries 423.2.2 Second-Order Consensus in Strongly Connected Networks 453.2.3 Second-Order Consensus in Rooted Networks 503.2.4 Simulation Examples 533.3 Notes 544 Higher-Order Consensus in Multi-agent Systems 564.1 Preliminaries 564.2 Higher-Order Consensus in a General Form 584.2.1 Synchronization in Complex Networks 584.2.2 Higher-Order Consensus in a General Form 594.2.3 Consensus Region in Higher-Order Consensus 604.3 Leader-Follower Control in Multi-agent Systems 644.3.1 Leader-Follower Control in Multi-agent Systems with Full-State Feedback 654.3.2 Leader-Follower Control with Observers 674.4 Simulation Examples 694.4.1 Consensus Regions 694.4.2 Leader-Follower Control with Full-State Feedback 704.4.3 Leader-Follower Control with Observers 704.5 Notes 715 Stability Analysis of Swarming Behaviors 735.1 Preliminaries 735.2 Analysis of Swarm Cohesion 765.3 Swarm Cohesion in a Noisy Environment 805.4 Cohesion in Swarms with Switched Topologies 825.5 Cohesion in Swarms with Changing Topologies 845.6 Simulation Examples 935.7 Notes 956 Distributed Leader-Follower Flocking Control 966.1 Preliminaries 966.1.1 Model Formulation 976.1.2 Nonsmooth Analysis 996.2 Distributed Leader-Follower Control with Pinning Observers 1036.3 Simulation Examples 1106.4 Notes 1147 Consensus of Multi-agent Systems with Sampled Data Information 1157.1 Problem Statement 1167.2 Second-Order Consensus of Multi-agent Systems with Sampled Full Information 1177.2.1 Second-Order Consensus of Multi-agent Systems with Sampled Full Information 1197.2.2 Selection of Sampling Periods 1227.2.3 Design of Coupling Gains 1237.2.4 Consensus Region for the Network Spectrum 1257.2.5 Second-Order Consensus in Delayed Undirected Networks with Sampled Position and Velocity Data 1257.2.6 Simulation Examples 1287.3 Second-Order Consensus of Multi-agent Systems with Sampled Position Information 1327.3.1 Second-Order Consensus in Multi-agent Dynamical Systems with Sampled Position Data 1327.3.2 Simulation Examples 1397.4 Consensus of Multi-agent Systems with Nonlinear Dynamics and Sampled Information 1427.4.1 The Case with a Fixed and Strongly Connected Topology 1457.4.2 The Case with Topology Containing a Directed Spanning Tree 1497.4.3 The Case with Topology Having no Directed Spanning Tree 1557.5 Notes 1588 Consensus of Second-Order Multi-agent Systems with Intermittent Communication 1598.1 Problem Statement 1598.2 The Case with a Strongly Connected Topology 1618.3 The Case with a Topology Having a Directed Spanning Tree 1658.4 Consensus of Second-Order Multi-agent Systems with Nonlinear Dynamics and Intermittent Communication 1678.5 Notes 1729 Distributed Adaptive Control of Multi-agent Systems 1749.1 Distributed Adaptive Control in Complex Networks 1759.1.1 Preliminaries 1759.1.2 Distributed Adaptive Control in Complex Networks 1769.1.3 Pinning Edges Control 1789.1.4 Simulation Examples 1819.2 Distributed Control Gains Design for Second-Order Consensus in Nonlinear Multi-agent Systems 1839.2.1 Preliminaries 1849.2.2 Distributed Control Gains Design: Leaderless Case 1869.2.3 Distributed Control Gains Design: Leader-Follower Case 1909.2.4 Simulation Examples 1949.3 Notes 19610 Distributed Consensus Filtering in Sensor Networks 19810.1 Preliminaries 19910.2 Distributed Consensus Filters Design for Sensor Networks with Fully-Pinned Controllers 20110.3 Distributed Consensus Filters Design for Sensor Networks with Pinning Controllers 20510.4 Distributed Consensus Filters Design for Sensor Networks with Pinning Observers 20710.5 Simulation Examples 21010.6 Notes 21311 Delay-Induced Consensus and Quasi-Consensus in Multi-agent Systems 21411.1 Problem Statement 21411.2 Delay-Induced Consensus and Quasi-Consensus in Multi-agent Dynamical Systems 21711.3 Motivation for Quasi-Consensus Analysis 22311.4 Simulation Examples 22411.5 Notes 22812 Conclusions and FutureWork 22912.1 Conclusions 22912.2 Future Work 230Bibliography 232Index 241