A Necessary Condition for Network Identifiability With Partial Excitation and Measurement

Xiaodong Cheng*, Shengling Shi, Ioannis Lestas, Paul M.J. Van den Hof

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

This article considers dynamic networks where vertices and edges represent manifest signals and causal dependencies among the signals, respectively. We address the problem of how to determine if the dynamics of a network can be identified when only partial vertices are measured and excited. A necessary condition for network identifiability is presented, where the analysis is performed based on identifying the dependency of a set of rational functions from excited vertices to measured ones. This condition is further characterized by using an edge-removal procedure on the associated bipartite graph. Moreover, on the basis of necessity analysis, we provide a necessary and sufficient condition for identifiability in circular networks.
Original languageEnglish
Pages (from-to)6820-6827
Number of pages8
JournalIEEE Transactions on Automatic Control
Volume68
Issue number11
DOIs
Publication statusPublished - Nov 2023

Keywords

  • Bipartite graph
  • data-driven modeling
  • directed graphs
  • graph theory
  • network systems
  • system identification

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