Fault Diagnosability Analysis of Two-Dimensional Linear Discrete Systems

Dong Zhao, Choon Ki Ahn, Wojciech Paszke, Fangzhou Fu, Yueyang Li

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


In this article, a systematic fault diagnosability evaluation, including fault detectability and isolability, is established in a quantitative manner for two-dimensional systems. With ingenious data formulation, a parity relation of two-dimensional systems is first established, then the Kullback-Leibler divergence is employed as the key measure for the diagnosability analysis based on the established parity relation. The basic idea is to quantify the distribution differences among each fault scenario-related system dynamic behavior. Explicit necessary and sufficient condition for fault diagnosability is further derived based on the appropriately introduced definitions corresponding to the two directions evolving system properties. Finally, the effectiveness of the proposed method is verified by two examples.

Original languageEnglish
Article number9061045
Pages (from-to)826-832
Number of pages7
JournalIEEE Transactions on Automatic Control
Issue number2
Publication statusPublished - 2021 Feb


  • Fault detectability
  • Kullback-Leibler divergence
  • fault isolability
  • parity relation
  • two-dimensional systems

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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