Reconstructing tree structures of dynamic systems with hidden nodes under nonlinear dynamics

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The article tackles the problem of inferring information about the unknown structure of a network of dynamic systems under the assumption that the systems are connected according to a tree topology. In particular, the article introduces methodologies to address the presence of hidden (unmeasured) nodes in a scenario where only non-invasive observations are available. By non-invasive observations, it is meant that no known input signal is actively injected into the network. The whole system instead is assumed to be forced by unknown external excitations modeled as stochastic processes. No a priori assumption is made about the number and location of the hidden nodes. Current approaches are capable of consistently inferring the network structure from data, when the dynamics are linear and/or the measurements have a jointly Gaussian distribution. This work provides an approach that can also be applied to networks with nonlinear dynamics and non-Gaussian disturbances. Sufficient conditions are found under which a consistent reconstruction of the topology can be obtained.

Original languageEnglish (US)
Title of host publication24th Mediterranean Conference on Control and Automation, MED 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1331-1336
Number of pages6
ISBN (Electronic)9781467383455
DOIs
StatePublished - Aug 5 2016
Externally publishedYes
Event24th Mediterranean Conference on Control and Automation, MED 2016 - Athens, Greece
Duration: Jun 21 2016Jun 24 2016

Publication series

Name24th Mediterranean Conference on Control and Automation, MED 2016

Other

Other24th Mediterranean Conference on Control and Automation, MED 2016
Country/TerritoryGreece
CityAthens
Period6/21/166/24/16

Keywords

  • Estimation
  • Identification
  • Systems on a Graph

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