2020
DOI: 10.1109/tsipn.2020.2967145
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Recovering the Structural Observability of Composite Networks via Cartesian Product

Abstract: Observability is a fundamental concept in system inference and estimation. This paper is focused on structural observability analysis of Cartesian product networks. Cartesian product networks emerge in variety of applications including in parallel and distributed systems. We provide a structural approach to extend the structural observability of the constituent networks (referred as the factor networks) to that of the Cartesian product network. The structural approach is based on graph theory and is generic. W… Show more

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Cited by 5 publications
(1 citation statement)
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“…In fact, due to the geographically distributed nature of these systems, it is often desirable that structural controllability is assessed in a distributed fashion (Carvalho et al, 2017). In Doostmohammadian (2020), conditions to achieve the minimum number of sensors attaining structural observability are provided leveraging Cartesian product representation. Subsequently, we can pose the problem of determining structural changes ∆i,j (with the same dimensions of Āi,j ) that will change the interconnection between the different subsystems yielding structural controllability.…”
Section: Dynamics Design Problem To Attain Structural Controllabilitymentioning
confidence: 99%
“…In fact, due to the geographically distributed nature of these systems, it is often desirable that structural controllability is assessed in a distributed fashion (Carvalho et al, 2017). In Doostmohammadian (2020), conditions to achieve the minimum number of sensors attaining structural observability are provided leveraging Cartesian product representation. Subsequently, we can pose the problem of determining structural changes ∆i,j (with the same dimensions of Āi,j ) that will change the interconnection between the different subsystems yielding structural controllability.…”
Section: Dynamics Design Problem To Attain Structural Controllabilitymentioning
confidence: 99%