Ren / Cao Distributed Coordination of Multi-agent Networks

Emergent Problems, Models, and Issues
1. Auflage 2010
ISBN: 978-0-85729-169-1
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 310 Seiten

Reihe: Communications and Control Engineering

Distributed Coordination of Multi-agent Networks introduces problems, models, and issues such as collective periodic motion coordination, collective tracking with a dynamic leader, and containment control with multiple leaders, and explores ideas for their solution. Solving these problems extends the existing application domains of multi-agent networks; for example, collective periodic motion coordination is appropriate for applications involving repetitive movements, collective tracking guarantees tracking of a dynamic leader by multiple followers in the presence of reduced interaction and partial measurements, and containment control enables maneuvering of multiple followers by multiple leaders.

Wei Ren received the B.S. degree in electrical engineering from Hohai University, China, in 1997, the M.S. degree in mechatronics from Tongji University, China, in 2000, and the Ph.D. degree in electrical engineering from Brigham Young University, Provo, UT, in 2004. From October 2004 to July 2005, he was a Postdoctoral Research Associate with the Department of Aerospace Engineering, University of Maryland, College Park. Since August 2005, he has been with the Department of Electrical and Computer Engineering, Utah State University, Logan, where he is currently an Associate Professor. He is an author of the book Distributed Consensus in Multi-Vehicle Cooperative Control (Springer-Verlag, 2008). His research focuses on distributed control of multi-agent systems, networked cyber-physical systems, and autonomous control of unmanned vehicles. Dr. Ren was a recipient of the National Science Foundation CAREER Award in 2008. He is currently an Associate Editor for Systems and Control Letters and an Associate Editor on the IEEE Control Systems Society Conference Editorial Board.
Yongcan Cao received the B.S. degree from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2003 and the M.S. degree from Shanghai Jiao Tong University, Shanghai, China, in 2006, and the Ph.D. degree from Utah State University, Logan, in 2010, all in electrical engineering. His research interest focuses on cooperative control and information consensus of multi-agent systems.

Autoren/Hrsg.

Ren, Wei

Cao, Yongcan

Inhaltsverzeichnis

1;Preface;7
2;Acknowledgements;9
3;Contents;12
4;Preliminaries and Literature Review;17
4.1;Preliminaries;18
4.1.1;Notations;18
4.1.2;Algebraic Graph Theory Background;20
4.1.3;Algebra and Matrix Theory Background;24
4.1.4;Linear and Nonlinear System Theory Background;28
4.1.5;Nonsmooth Analysis Background;32
4.1.6;Time-delay System Theory Background;34
4.1.7;Notes;36
4.2;Overview of Recent Research in Distributed Multi-agent Coordination;37
4.2.1;Introduction;37
4.2.2;Consensus;39
4.2.2.1;Delay Effect;40
4.2.2.2;Convergence Speed;41
4.2.2.3;Stochastic Setting;41
4.2.2.4;Complex Systems;42
4.2.2.5;Quantization;43
4.2.2.6;Sampled-data Setting;43
4.2.2.7;Finite-time Convergence;43
4.2.2.8;Asynchronous Effect;44
4.2.3;Distributed Formation Control;44
4.2.3.1;Formation Producing;44
4.2.3.1.1;Matrix Theory Approach;44
4.2.3.1.2;Lyapunov-based Approach;45
4.2.3.1.3;Graph Rigidity Approach;45
4.2.3.1.4;Receding Horizon Approach;46
4.2.3.2;Formation Tracking;46
4.2.3.2.1;Matrix Theory Approach;46
4.2.3.2.2;Potential Function Approach;47
4.2.3.2.3;Lyapunov-based Approach;47
4.2.3.2.4;Other Approaches;47
4.2.3.3;Connectivity Maintenance;48
4.2.3.4;Controllability;48
4.2.4;Distributed Optimization;49
4.2.4.1;Individual Cost Functions;49
4.2.4.2;Global Cost Functions;49
4.2.5;Distributed Task Assignment;50
4.2.5.1;Coverage Control;50
4.2.5.2;Scheduling;51
4.2.5.3;Surveillance;52
4.2.6;Distributed Estimation and Control;52
4.2.7;Intelligent Coordination;53
4.2.7.1;Pursuer-invader Problem;53
4.2.7.2;Game Theory;54
4.2.8;Discussion;54
4.2.9;Notes;55
5;Emergent Problems in Distributed Multi-agent Coordination;56
5.1;Collective Periodic Motion Coordination;57
5.1.1;Cartesian Coordinate Coupling;57
5.1.1.1;Single-integrator Dynamics;58
5.1.1.2;Double-integrator Dynamics;63
5.1.1.3;Simulation;72
5.1.2;Coupled Harmonic Oscillators;74
5.1.2.1;Problem Statement;75
5.1.2.2;Convergence Under Directed Fixed Interaction;76
5.1.2.3;Convergence Under Directed Switching Interaction;81
5.1.2.4;Application to Motion Coordination in Multi-agent Systems;84
5.1.3;Notes;86
5.2;Collective Tracking with a Dynamic Leader;88
5.2.1;Problem Statement;88
5.2.2;Collective Tracking for Single-integrator Dynamics;89
5.2.2.1;Coordinated Tracking Under Fixed and Switching Interaction;89
5.2.2.2;Swarm Tracking Under Switching Interaction;94
5.2.3;Collective Tracking for Double-integrator Dynamics;96
5.2.3.1;Coordinated Tracking when the Leader's Velocity is Varying;96
5.2.3.2;Coordinated Tracking when the Leader's Velocity is Constant;102
5.2.3.3;Swarm Tracking when the Leader's Velocity is Constant;103
5.2.3.4;Swarm Tracking when the Leader's Velocity is Varying;104
5.2.4;Simulation;107
5.2.5;Notes;115
5.3;Containment Control with Multiple Leaders;119
5.3.1;Problem Statement;119
5.3.2;Stability Analysis for Multiple Stationary Leaders;121
5.3.2.1;Directed Fixed Interaction;121
5.3.2.2;Directed Switching Interaction;123
5.3.2.3;Simulation;130
5.3.3;Stability Analysis for Multiple Dynamic Leaders;132
5.3.3.1;Directed Fixed Interaction;133
5.3.3.2;Directed Switching Interaction;137
5.3.3.3;Simulation;142
5.3.4;Containment Control with Swarming Behavior;142
5.3.4.1;Algorithm Design;143
5.3.4.2;Analysis for Multiple Stationary Leaders;145
5.3.4.3;Analysis for Multiple Dynamic Leaders;147
5.3.4.4;Simulation;151
5.3.5;Notes;154
6;Emergent Models in Distributed Multi-agent Coordination;155
6.1;Networked Lagrangian Systems;156
6.1.1;Problem Statement;156
6.1.2;Distributed Leaderless Coordination for Networked Lagrangian Systems;158
6.1.2.1;Fundamental Algorithm;159
6.1.2.2;Nonlinear Algorithm;161
6.1.2.3;Algorithm Accounting for Unavailability of Measurements of Generalized Coordinate Derivatives;164
6.1.2.4;Simulation;166
6.1.3;Distributed Coordinated Regulation and Tracking for Networked Lagrangian Systems;170
6.1.3.1;Coordinated Regulation when the Leader's Vector of Generalized Coordinates is Constant;171
6.1.3.2;Coordinated Tracking when the Leader's Vector of Generalized Coordinate Derivatives is Constant;174
6.1.3.2.1;Model-dependent Coordinated Tracking Algorithm;175
6.1.3.2.2;Coordinated Tracking Algorithm Accounting for Parametric Uncertainties;180
6.1.3.3;Coordinated Tracking when the Leader's Vector of Generalized Coordinate Derivatives is Varying;183
6.1.3.4;Simulation;189
6.1.4;Notes;190
6.2;Networked Fractional-order Systems;193
6.2.1;Problem Statement;193
6.2.2;Stability Analysis of a Coordination Algorithm for Networked Fractional-order;196
6.2.2.1;Directed Fixed Interaction;196
6.2.2.2;Directed Switching Interaction;200
6.2.2.3;Simulation;202
6.2.3;Stability Analysis of Fractional-order Coordination Algorithms with Absolute/Relative Damping for Networked Fractional-order Systems;205
6.2.3.1;Absolute Damping;205
6.2.3.2;Relative Damping;207
6.2.3.3;Simulation;210
6.2.4;Notes;212
7;Emergent Issues in Distributed Multi-agent Coordination;213
7.1;Sampled-data Setting;214
7.1.1;Sampled-data Coordinated Tracking for Single-integrator Dynamics;214
7.1.1.1;Algorithm Design;215
7.1.1.2;Convergence Analysis of the Proportional-derivative-like Discrete-time Coordinated Tracking Algorithm;216
7.1.1.3;Comparison Between the Proportional-like and Proportional-derivative-like Discrete-time Coordinated Tracking Algorithms;220
7.1.1.4;Simulation;222
7.1.2;Sampled-data Coordination for Double-integrator Dynamics Under Fixed Interaction;224
7.1.2.1;Coordination Algorithms with Absolute and Relative Damping;224
7.1.2.2;Convergence Analysis of the Sampled-data Coordination Algorithm with Absolute Damping;225
7.1.2.3;Convergence Analysis of the Sampled-data Coordination Algorithm with Relative Damping;231
7.1.2.4;Simulation;235
7.1.3;Sampled-data Coordination for Double-integrator Dynamics Under Switching Interaction;237
7.1.3.1;Convergence Analysis of the Sampled-data Coordination Algorithm with Absolute Damping;238
7.1.3.2;Convergence Analysis of the Sampled-data Coordination Algorithm with Relative Damping;241
7.1.3.3;Simulation;244
7.1.4;Notes;247
7.2;Optimality Aspect;248
7.2.1;Problem Statement;248
7.2.2;Optimal Linear Coordination Algorithms in a Continuous-time Setting from a Linear Quadratic Regulator Perspective;250
7.2.2.1;Optimal State Feedback Gain Matrix Using the Interaction-free Cost Function;251
7.2.2.2;Optimal Scaling Factor Using the Interaction-related Cost Function;254
7.2.2.3;Illustrative Examples;257
7.2.3;Optimal Linear Coordination Algorithms in a Discrete-time Setting from a Linear Quadratic Regulator Perspective;258
7.2.3.1;Optimal State Feedback Gain Matrix Using the Interaction-free Cost Function;258
7.2.3.2;Optimal Scaling Factor Using the Interaction-related Cost Function;266
7.2.3.3;Illustrative Examples;267
7.2.4;Notes;268
7.3;Time Delay;269
7.3.1;Problem Statement;269
7.3.2;Coordination for Single-integrator Dynamics with Communication and Input Delays Under Directed Fixed Interaction;270
7.3.2.1;Leaderless Coordination;270
7.3.2.2;Coordinated Regulation when the Leader's Position is Constant;274
7.3.2.3;Coordinated Tracking with Full Access to the Leader's Velocity;276
7.3.2.4;Coordinated Tracking with Partial Access to the Leader's Velocity;279
7.3.3;Coordination for Double-integrator Dynamics with Communication and Input Delays Under Directed Fixed Interaction;280
7.3.3.1;Leaderless Coordination;280
7.3.3.2;Coordinated Tracking when the Leader's Velocity is Constant;283
7.3.3.3;Coordinated Tracking with Full Access to the Leader's Acceleration;286
7.3.3.4;Coordinated Tracking with Partial Access to the Leader's Acceleration;288
7.3.4;Simulation;290
7.3.5;Notes;293
8;References;296
9;Index;310