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Controllability, Identification, and Randomness in Distributed Systems (Springer Theses)

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This interdisciplinary thesis involves the design and analysis of coordination algorithms on networks, identification of dynamic networks and estimation on networks with random geometries with implications for networks that support the operation of dynamic systems, e.g., formations of robotic vehicles, distributed estimation via sensor networks. The results have ramifications for fault detection and isolation of large-scale networked systems and optimization models and algorithms for next generation aircraft power systems. The author finds novel applications of the methodology in energy systems, such as residential and industrial smart energy management systems.
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Specificații

ISBN-13: 9783319024288
ISBN-10: 3319024280
Pagini: 190
Ilustrații: 40 illus., 10 illus. in color
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.44 kg
Ediția: 2014
Editura: Springer
Colecția Springer
Seria Springer Theses

Locul publicării: Cham, Switzerland

Public țintă

Research

Cuprins

Background.- Part I: Can One Hear the Shape of Coordination?.- Network Identification via Node Knock-out.- A Sieve Method for Consensus-Type Network Tomography.- Network Identification via Graph Realization.- Part II: Controllability over Networks.- Controllability and Observability of Circulant Networks.- Controllability Gramian, Symmetry Structures and Application of Circulant Networks.- Controllability and Observability of Path Networks.- Part III: System Properties of Stochastic Networks.- System Properties of Stochastic Networks: Controllability and Optimality.- Coordinated Decentralized Estimation over Random Networks.- Online Coordinated Decentralized Localization of the Seaglider with Intermittent Observations.- Social Control and Optimal Marketing.- Concluding Remarks and Future Directions.

Notă biografică

Dr. Marzieh Nabi-Abdolyouse is currently at the Palo Alto Research Center (PARC), having graduated with a PhD in Distributed Space Systems Lab (DSSL) and a M.Sc. in Mathematics with specialty in probability and optimization, from the University of Washington.

Textul de pe ultima copertă

This interdisciplinary thesis involves the design and analysis of coordination algorithms on networks, identification of dynamic networks, and estimation on networks with random geometries with implications for networks that support the operation of dynamic systems, e.g., formations of robotic vehicles, distributed estimation via sensor networks.   The results have ramifications for fault detection and isolation of large-scale networked systems and optimization models and algorithms for next generation aircraft power systems.  The author  finds novel applications of the methodology in energy systems, such as residential and industrial smart energy management systems.

Caracteristici

Nominated by the University of Washington as an outstanding Ph.D. thesis
Demonstrates how a diffusion-based network can be controlled or observed by external entities in presence of randomness in the network’s structure or the underlying observation and control
Mechanisms
Presents results on the identification of dynamic networks, which involves observing the behavior of networks with the aim of identifying their internal structure
Analyzes distributed optimization models and their convergence properties for energy management and optimization