Abstract: Distributed estimation is where a network of agents is tasked to
estimate the state of a dynamical system. Agents only communicate over a sparse
communication network. Recently, consensus-based estimation has been proposed as a
distributed solution of this problem where the agents implement a large number of
information exchanges between every two successive time-steps of the system ... read moredynamics. For
optimal performance, this consensus-based estimator requires a consensus to be reached
first. When the network is unable to implement a consensus due to, e.g.,
resource-constraints or faster system dynamics, distributed solutions have been proposed
with single-time information exchanges. In this scenario both system dynamics and
distributed estimator evolve at the same time-scale. This scenario requires the system to
be observable at every estimator/agent, implying the new concept of distributed
observability. Given this background, this thesis is devoted to (1) formulation of
distributed observability in single-time scale estimation, (2) partitioning the necessary
set of state measurements based on their role in distributed observability, and (3)
characterization of necessary and sufficient connectivity of the underlying communication
network topology among the agents. Employing structure-based generic methodology instead of
algebraic approaches motivates application in power systems and social
Thesis (Ph.D.)--Tufts University, 2015.
Submitted to the Dept. of Electrical Engineering.
Advisor: Usman Khan.
Committee: Brian Tracy, Carlo Fischione, Alexander Stankovic, and Jason
Keywords: Electrical engineering, and Mathematics.read less