Subspace identification of local systems in 1D homogeneous networks

Chengpu Yu, Michel Verhaegen, A. Hansson

Research output: Contribution to journalArticleScientificpeer-review

6 Citations (Scopus)

Abstract

This note considers the identification of large-scale 1D networks consisting of identical LTI dynamical systems. A subspace identification method is developed that only uses local input-output information and does not rely on knowledge about the local state interaction. The proposed identification method estimates the Markov parameters of a locally lifted system, following the state-space realization of a single subsystem. The Markov-parameter estimation is formulated as a rank minimization problem by exploiting the low-rank property and a two-layer Toeplitz structural property in the data equation, while the state-space realization of a single subsystem is formulated as a structured low-rank matrix factorization problem. The effectiveness of the proposed identification method is demonstrated by simulation examples.
Original languageEnglish
Pages (from-to)1126-1131
JournalIEEE Transactions on Automatic Control
Volume63 (2018)
Issue number4
DOIs
Publication statusPublished - 2017

Keywords

  • Large-scale 1D distributed systems
  • rank minimization problem
  • two-layer Toeplitz structure

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