Subspace identification of individual systems in a large-scale heterogeneous network

Chengpu Yu, Jie Chen, Michel Verhaegen

Research output: Contribution to journalArticleScientificpeer-review

27 Citations (Scopus)

Abstract

This paper considers the identification of a network consisting of discrete-time LTI systems that are interconnected by their unmeasurable states. For a large-scale network, the computational burden prevents a centralized solution. To cope with this problem, a subspace-based local identification approach using local observations is presented, which consists of subspace intersection operations in both the temporal and spatial domains. Sufficient conditions are provided for the consistent identification of the presented identification approach. Finally, the implementation of this approach on 1D network is specially investigated and numerical simulations are provided to show its effectiveness.

Original languageEnglish
Article number108517
Number of pages13
JournalAutomatica
Volume109
DOIs
Publication statusPublished - 2019

Keywords

  • Errors-in-variables model
  • Large-scale network
  • Subspace identification

Fingerprint Dive into the research topics of 'Subspace identification of individual systems in a large-scale heterogeneous network'. Together they form a unique fingerprint.

  • Cite this