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Semi-autonomous networkseffective co...

Chapman, Airlie.

Semi-autonomous networkseffective control of networked systems through protocols, design, and modeling /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Semi-autonomous networksby Airlie Chapman.
Reminder of title:	effective control of networked systems through protocols, design, and modeling /
Author:	Chapman, Airlie.
Published:	Cham :Springer International Publishing :2015.
Description:	xxxi, 187 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Intelligent control systemsMathematical models.
Online resource:	http://dx.doi.org/10.1007/978-3-319-15010-9
ISBN:	9783319150109 (electronic bk.)

Semi-autonomous networkseffective control of networked systems through protocols, design, and modeling /
Chapman, Airlie.

Semi-autonomous networkseffective control of networked systems through protocols, design, and modeling /[electronic resource] :by Airlie Chapman. - Cham :Springer International Publishing :2015. - xxxi, 187 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..

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.

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.

ISBN: 9783319150109 (electronic bk.)

Standard No.: 10.1007/978-3-319-15010-9doiSubjects--Topical Terms:

714533
Intelligent control systems
--Mathematical models.

LC Class. No.: TJ217.5

Dewey Class. No.: 629.8015118

Semi-autonomous networkseffective control of networked systems through protocols, design, and modeling /
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300 $a xxxi, 187 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer theses, $x 2190-5053
505 0 $a 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.
520 $a 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.
650 0 $a Intelligent control systems $x Mathematical models. $3 714533
650 0 $a Network analysis (Planning) $3 191657
650 0 $a Control theory. $3 182248
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650 2 4 $a Control. $3 349080
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950 $a Physics and Astronomy (Springer-11651)