E-Book, Englisch, 124 Seiten, eBook
Zhu / Martínez Distributed Optimization-Based Control of Multi-Agent Networks in Complex Environments
2015
ISBN: 978-3-319-19072-3
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 124 Seiten, eBook
Reihe: SpringerBriefs in Control, Automation and Robotics
ISBN: 978-3-319-19072-3
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
This book offers a concise and in-depth exposition of specific algorithmic solutions for distributed optimization based control of multi-agent networks and their performance analysis. It synthesizes and analyzes distributed strategies for three collaborative tasks: distributed cooperative optimization, mobile sensor deployment and multi-vehicle formation control. The book integrates miscellaneous ideas and tools from dynamic systems, control theory, graph theory, optimization, game theory and Markov chains to address the particular challenges introduced by such complexities in the environment as topological dynamics, environmental uncertainties, and potential cyber-attack by human adversaries.
The book is written for first- or second-year graduate students in a variety of engineering disciplines, including control, robotics, decision-making, optimization and algorithms and with backgrounds in aerospace engineering, computer science, electrical engineering, mechanical engineering and operations research. Researchers in these areas may also find the book useful as a reference.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Weitere Infos & Material
1 Preliminaries.- 1.1 Basic Notations.- 1.2 The Consensus Problem.- 1.3 Convex Optimization.- 1.4 Non-Cooperative Game Theory.- 1.5 Markov Chains.- 1.6 Notes.- 2 Distributed Cooperative Optimization.- 2.1 Introduction.- 2.2 Problem Formulation.- 2.3 Case (I): Absence of Equality Constraint.- 2.4 Case (Ii): Identical Local Constraint Sets.- 2.5 Appendix.- 2.6 Notes.- 3 Game Theoretic Optimal Sensor Deployment.- 3.1 Introduction.- 3.2 Problem Formulation.- 3.3 Distributed Learning Algorithms.- 3.4 Convergence Analysis.- 3.5 Numerical Examples.- 3.6 Notes.- 4 Distributed Resilient Formation Control.- 4.1 Introduction.- 4.2 Problem Formulation.- 4.3 Preliminaries.- 4.4 Distributed Attack-Resilient Algorithm.- 4.5 Convergence Analysis.- 4.6 Discussion.- 4.7 Numerical Examples.- 4.8 Notes.- Index.- References.




