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Physics - Complexity | Controllability, Identification, and Randomness in Distributed Systems

Controllability, Identification, and Randomness in Distributed Systems

Series: Springer Theses

Nabi, Marzieh

2014, XVII, 151 p. 39 illus., 30 illus. in color.

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  • 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
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.

Content Level » Research

Keywords » Cartesian Product Networks - Circulant Networks - Controllability Gramian - Fault Detection - Linear Quadratic Regulator - Network Identification - Network Tomography - Node Knockout - Path Networks - Stochastic Systems - Underwater Acoustic Ranging

Related subjects » Complexity - Control Engineering - Mechanical Engineering - Policy, Economics, Management & Transport

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