Nonlinear graph-based theory for dynamical network observability

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dc.creatorChristophe Letellier
dc.creatorIrene Sendiña-Nadal
dc.creatorLuis Antonio Aguirre
dc.date.accessioned2025-04-22T12:56:40Z
dc.date.accessioned2025-09-09T01:21:36Z
dc.date.available2025-04-22T12:56:40Z
dc.date.issued2018
dc.identifier.doi10.1103/PhysRevE.98.020303
dc.identifier.issn24700045
dc.identifier.urihttps://hdl.handle.net/1843/81722
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofPhysical Review E
dc.rightsAcesso Restrito
dc.subjectSistemas não lineares
dc.subject.otherIn a large complex systems, observability becomes a key concept that addresses the ability to examine the system dynamics from a reduced set of measurements collected over a finite time
dc.titleNonlinear graph-based theory for dynamical network observability
dc.typeArtigo de periódico
local.citation.issue2
local.citation.spage020303
local.citation.volume98
local.description.resumoA faithful description of the state of a complex dynamical network would require, in principle, the measurement of all its 𝑑 variables, an infeasible task for high dimensional systems due to practical limitations. However the network dynamics might be observable from a reduced set of measured variables but how to reliably identify the minimum set of variables providing full observability still remains an unsolved problem. In order to tackle this issue from the Jacobian matrix of the governing equations, we construct a pruned fluence graph in which the nodes are the state variables and the links represent only the linear dynamical interdependences after having ignored the nonlinear ones. From this graph, we identify the largest connected subgraphs with no outgoing links in which every node can be reached from any other node in the subgraph. In each one of them, at least one node must be measured to correctly monitor the state of the system in a 𝑑-dimensional reconstructed space. Our procedure is here tested by investigating large-dimensional reaction networks. Our results are validated by comparing them with the determinant of the observability matrix which provides a rigorous assessment of the system's observability.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://journals.aps.org/pre/abstract/10.1103/PhysRevE.98.020303

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