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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.
List of contents
Nomenclature.- Acknowledgments.- Dedication.- Supervisor's Foreword.- Introduction.- Preliminaries.- Notation.- Network Topology.- Consensus Dynamics.- Advection on Graphs.- Beyond Linear Protocols.- Measures and Rewiring.- Distributed Online Topology Design for Disturbance Rejection.- Network Topology Design for UAV Swarming with Wind Gusts.- Cartesian Products of Z-Matrix Networks: Factorization and Interval Analysis.- On the Controllability and Observability of Cartesian Product Networks.- Strong Structural Controllability of Networked Dynamics.- Security and Infiltration of Networks: A Structural Controllability and Observability Perspective.- Conclusion and Future Work.- Appendix.- Single Anchor State Measures.
About the author
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.
