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E-Book

E-Book, Englisch, 187 Seiten, eBook

Reihe: Springer Theses

Chapman Semi-Autonomous Networks

Effective Control of Networked Systems through Protocols, Design, and Modeling
2015
ISBN: 978-3-319-15010-9
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

Effective Control of Networked Systems through Protocols, Design, and Modeling

E-Book, Englisch, 187 Seiten, eBook

Reihe: Springer Theses

ISBN: 978-3-319-15010-9
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark



This thesis analyzes and explores the design of controlled networked dynamic systems - dubbed semi-autonomous networks. The work approaches the problem of effective control of semi-autonomous networks from three fronts: protocols which are run on individual agents in the network; the network interconnection topology design; and efficient modeling of these often large-scale networks. The author extended the popular consensus protocol to advection and nonlinear consensus. The network redesign algorithms are supported by a game-theoretic and an online learning regret analysis.

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Research


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Weitere Infos & Material


Nomenclature

Acknowledgments

Dedication

Supervisor's Foreword

Introduction
Preliminaries
Notation

Network Topology
Consensus Dynamics

Part 1. Beyond Linear Consensus

Chapter 1. Advection on Graphs

1.1. Introduction

1.2. Advection Properties

1.3. Examples

1.4. Remarks

Chapter 2. Beyond Linear Protocols
2.1. Introduction
2.2. Model
2.3. Equilibria and Convergence
2.4. Extension
2.5. Remarks

Part 2. Network Measures and Adaptive Topologies

Chapter 3. Measures and Rewiring
3.1. Introduction
3.2. Leader-Follower Consensus Dynamics
3.3. Mean Tracking Measure
3.4. Variance Damping Measure
3.5. Fusing Adaptive Protocols
3.6. Remarks

Chapter 4. Distributed Online Topology Design for Disturbance Rejection
4.1. Introduction
4.2. Online Convex Optimization
4.3. Model and Measure
4.4. Distributed Online Topology Design Algorithm
4.5. Remarks

Chapter 5. Network Topology Design for UAV Swarming with Wind Gusts
5.1. Introduction
5.2. Model
5.3. Open Loop H2 Norm
5.4. Topology Design
5.5. Remarks

Part 3. Cartesian Product Networks

Chapter 6. Cartesian Products of Z-Matrix Networks: Factorization and Interval
Analysis

6.1. Introduction
6.2. Cartesian Product
6.3. Z-matrix Dynamics
6.4. Interval Matrices
6.5. Z-Matrix Dynamics over Cartesian Products of Digraphs
6.6. Remarks

Chapter 7. On the Controllability and Observability of Cartesian Product Networks
7.1. Introduction
7.2. Digraph Automorphisms
7.3. Problem setup
7.4. Control Product
7.5. Layered Control
7.6. Filtering on Social Product Networks
7.7. Remarks

Part 4. Structural Controllability

Chapter 8. Strong Structural Controllability of Networked Dynamics
8.1. Introduction
8.2. Pattern Matrices
8.3. Model
8.4. Structural Controllability
8.5. Testing inputs for Strong S-Controllability
8.6. Finding Strongly S-Controllable Inputs
8.7. Remarks

Chapter 9. Security and Infiltration of Networks: A Structural Controllability and
Observability Perspective
9.1. Introduction
9.2. Weak Structural Controllability - A cautious lower bound
9.3. Strong Structural Controllability - Guaranteed Security
9.4. Remarks
Final Remarks

Chapter 10. Conclusion and Future Work
10.1. Concluding Remarks
10.2. Future Directions

Appendix
Single Anchor State Measures


Airlie Chapman received the Ph.D. degree from the William E. Boeing Aeronautics and Astronautics Department at the University of Washington, Seattle in 2013 and was simultaneously awarded the M.S. degree in mathematics. She received the B.S. degree in aeronautical (space) engineering and the M.S. degree in engineering research from the University of Sydney, Australia, in 2006 and 2008, respectively. She is currently a postdoctoral fellow at the University of Washington, Seattle. Dr. Chapman was awarded the College of Engineering Dean’s Fellowship at the University of Washington and is a two-time recipient of the Amelia Earhart Fellowship. Her research interests are networked dynamic systems and graph theory with applications to robotics and aerospace systems.



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