Gazi / Passino Swarm Stability and Optimization

1. Auflage 2011
ISBN: 978-3-642-18041-5
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 299 Seiten

Swarming species such as flocks of birds or schools of fish exhibit
fascinating collective behaviors during migration and predator
avoidance.  Similarly, engineered multi-agent dynamic systems such as groups of autonomous ground, underwater, or air vehicles ('vehicle swarms') exhibit sophisticated collective behaviors while maneuvering.
In this book we show how to model and control a wide range of such
multi-agent dynamic systems and analyze their collective behavior
using both stability theoretic and simulation-based approaches. In
particular, we investigate problems such as group aggregation, social
foraging, formation control, swarm tracking, distributed agreement,
and engineering optimization inspired by swarm behavior.

Autoren/Hrsg.

Gazi, Veysel

Passino, Kevin M.

Inhaltsverzeichnis

1;Title;1
2;Preface;5
3;Contents;10
4;Part I Basic Principles;15
4.1;Introduction;16
4.1.1; Swarms in Biology and Engineering;16
4.1.2; For Further Reading;22
4.1.2.1; Early Works in Biology;22
4.1.2.2; Early Works in Physics;24
4.1.2.3; Early Works in Engineering and Computer Science;25
4.2;Swarm Coordination and Control Problems;28
4.2.1; Aggregation;28
4.2.2; Social Foraging;30
4.2.3; Formation Control and Swarm Tracking;31
4.2.4; Distributed Agreement;33
4.2.5; Function Minimization;35
4.2.6; Related Problems and Behaviors and Further Reading;36
4.2.6.1; Formation Structure Breakdowns;36
4.2.6.2; Flocking;36
4.2.6.3; Rendezvous;37
4.2.6.4; Synchronization of Coupled Nonlinear Oscillators;37
4.2.6.5; Other Behaviors;38
5;Part II Continuous Time Swarms;39
5.1;Swarms of Single Integrator Agents;40
5.1.1; Single Integrator Agent Model;40
5.1.2; Aggregation;41
5.1.2.1; Potential Function Design;41
5.1.2.2; Analysis of Swarm Motion;43
5.1.2.3; Swarm Cohesion Analysis;46
5.1.2.4; Agents with Finite Body Size;52
5.1.2.5; Simulation Examples;55
5.1.3; Social Foraging;57
5.1.3.1; Introduction;57
5.1.3.2; Swarm Cohesion Analysis;59
5.1.3.3; Swarm Motion in Various Resource Profiles;62
5.1.3.4; Analysis of Individual Behavior in a Cohesive Swarm;70
5.1.3.5; Simulation Examples;71
5.1.4; Formation Control;75
5.1.4.1; Simulation Examples;77
5.1.5; Swarm Tracking;78
5.1.5.1; Simulation Examples;82
5.1.6; Further Issues;83
5.1.6.1; General Neighborhood Topology;83
5.1.6.2; Non-reciprocal Agent Interactions;84
5.1.6.3; For Further Reading;84
5.2;Swarms of Double Integrator Agents;85
5.2.1; Double Integrator Model;85
5.2.2; Stability Analysis of Swarm Cohesion Properties;86
5.2.2.1; Controls and Error Dynamics;87
5.2.2.2; Cohesive Social Foraging with Noise;91
5.2.2.3; Special Case: Identical Agents;103
5.2.3; Stability Analysis of Swarm Trajectory Following;109
5.2.4; Simulation Examples;112
5.2.4.1; No-Noise Case;112
5.2.4.2; Noise Case;112
5.2.5; Further Issues;115
5.2.5.1; Extensions and Generalizations;115
5.2.5.2; For Further Reading;115
5.3;Swarms of Fully Actuated Agents with Model Uncertainty;116
5.3.1; Fully Actuated Agent Model with Uncertainty;116
5.3.2; Controller Development;117
5.3.2.1; Aggregation, Foraging, and Formation Control;117
5.3.2.2; Swarm Tracking;120
5.3.3; Potential Functions and Bounds;123
5.3.3.1; Aggregation;123
5.3.3.2; Social Foraging;124
5.3.3.3; Formation Control;126
5.3.3.4; Swarm Tracking;126
5.3.4; Simulation Examples;127
5.3.4.1; Aggregation;128
5.3.4.2; Social Foraging;129
5.3.4.3; Formation Control;130
5.3.4.4; Swarm Tracking;131
5.3.5; Further Issues;132
5.3.5.1; Extensions and Generalizations;132
5.3.5.2; For Further Reading;132
5.4;Swarms of Non-holonomic Unicycle Agents with Model Uncertainty;133
5.4.1; Non-holonomic Unicycle Agent Model with Uncertainty;133
5.4.2; Controller Development;134
5.4.2.1; Aggregation, Foraging, and Formation Control;134
5.4.2.2; Swarm Tracking;139
5.4.3; Potential Functions and Bounds;142
5.4.3.1; Aggregation;142
5.4.3.2; Social Foraging;145
5.4.3.3; Formation Control;147
5.4.3.4; Swarm Tracking;147
5.4.4; Simulation Examples;149
5.4.4.1; Aggregation;150
5.4.4.2; Social Foraging;152
5.4.4.3; Formation Control;152
5.4.4.4; Swarm Tracking;153
5.4.5; Further Issues;154
5.4.5.1; Model Equivalence;154
5.4.5.2; Extensions and Generalizations;156
5.4.5.3; For Further Reading;156
5.5;Formation Control Using Nonlinear Servomechanism;158
5.5.1; General Non-linear Agent Model;158
5.5.2; Nonlinear Servomechanism Based Controller Development;161
5.5.2.1; Full Information Controller;162
5.5.2.2; Error Feedback Controller;163
5.5.3; Formation Reconfiguration;165
5.5.3.1; Expansion/Contraction;167
5.5.3.2; Rotation;167
5.5.3.3; Topology Change;168
5.5.4; Illustrative Examples;168
5.5.5; Further Issues;177
5.5.5.1; Extensions and Generalizations;177
5.5.5.2; For Further Reading;179
6;Part III Discrete Time Swarms;181
6.1;One-Dimensional Discrete-Time Swarm;182
6.1.1; The Swarm Model;182
6.1.1.1; Agent Model;182
6.1.1.2; One-Dimensional Swarm Model;183
6.1.2; The System under Total Synchronism;188
6.1.3; Asynchronous Swarm;194
6.1.4; Simulation Results;198
6.1.5; Further Issues;200
6.1.5.1; Extensions and Generalizations;200
6.1.5.2; For Further Reading;200
6.2;Asynchronous Distributed Agreement in Discrete Time Swarms;201
6.2.1; Model of the System;201
6.2.2; System under Total Synchronism;204
6.2.3; Asynchronous System;208
6.2.4; Simulation Examples;212
6.2.5; Further Issues;217
6.2.5.1; Application Areas of the Agreement Model;217
6.2.5.2; Extensions and Generalizations;218
6.2.5.3; For Further Reading;220
6.3;Formation Control with Potential Functions and Newton’s Iteration;222
6.3.1; Path Planning for a Single Agent;222
6.3.2; Controller Development;226
6.3.3; Simulation Examples;230
6.3.4; Further Issues;233
6.3.4.1; Extensions and Generalizations;233
6.3.4.2; For Further Reading;233
7;Part IV Swarm Based Optimization Methods;234
7.1;Bacteria Foraging Optimization;235
7.1.1; Bacterial Foraging by E. coli;235
7.1.1.1; Swimming and Tumbling;235
7.1.1.2; Chemotaxis and Climbing Nutrient Gradients;237
7.1.1.3; Underlying Sensing and Decision-Making Mechanisms;238
7.1.1.4; Elimination and Dispersal Events;239
7.1.2; E. coli Bacterial Foraging for Optimization;240
7.1.2.1; An Optimization Model for E. coli Bacterial Foraging;240
7.1.2.2; Bacterial Foraging Optimization Algorithm (BFOA);244
7.1.2.3; Guidelines for Algorithm Parameter Choices;246
7.1.2.4; Relations to the Genetic Algorithm;247
7.1.3; Example: Function Optimization via E. coli Foraging;247
7.1.3.1; Nutrient Hill-Climbing: No Swarming;248
7.1.3.2; Swarming Effects;249
7.1.4; Further Issues;250
7.1.4.1; Extensions and Generalizations;251
7.1.4.2; For Further Reading;251
7.2;Particle Swarm Optimization;252
7.2.1; Basic PSO Iteration;252
7.2.2; Synchronous and Asynchronous PSO Implementations;254
7.2.2.1; Traditional PSO Implementations;254
7.2.2.2; Decentralized Asynchronous PSO Formulation;256
7.2.3; Particle Neighborhoods;258
7.2.3.1; Static Neighborhood;258
7.2.3.2; Dynamic Neighborhood;260
7.2.3.3; Directed Graph Representation of Particle Neighborhoods;265
7.2.3.4; Connectivity of the Swarm;267
7.2.4; Simulation Examples;271
7.2.5; Further Issues;276
7.2.5.1; Extensions and Generalizations;278
7.2.5.2; For Further Reading;279
8;References;281
9;Index;295