Fault Diagnosability Analysis of Two-Dimensional Linear Discrete Systems

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

doi:10.1109/TAC.2020.2986054

Fault Diagnosability Analysis of Two-Dimensional Linear Discrete Systems

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

Research output: Contribution to journal › Article › peer-review

22 Citations (Scopus)

Abstract

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 language	English
Article number	9061045
Pages (from-to)	826-832
Number of pages	7
Journal	IEEE Transactions on Automatic Control
Volume	66
Issue number	2
DOIs	https://doi.org/10.1109/TAC.2020.2986054
Publication status	Published - 2021 Feb

Keywords

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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10.1109/TAC.2020.2986054

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title = "Fault Diagnosability Analysis of Two-Dimensional Linear Discrete Systems",

abstract = "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.",

keywords = "Fault detectability, Kullback-Leibler divergence, fault isolability, parity relation, two-dimensional systems",

author = "Dong Zhao and Ahn, {Choon Ki} and Wojciech Paszke and Fangzhou Fu and Yueyang Li",

note = "Funding Information: Manuscript received December 17, 2019; accepted March 29, 2020. Date of publication April 8, 2020; date of current version January 28, 2021. This work was supported in part by the National Natural Science Foundation of China under Grant 91948201, Grant 61973135, and Grant 61773242, in part by the Shandong Provincial Key Research and Development Program Major Scientific and Technological Innovation Project, China under Grant 2019JZZY010441, in part by the National Research Foundation of Korea grant funded by the Korea government (Ministry of Science and ICT) under Grant NRF-2020R1A2C1005449, and in part by the National Science Centre in Poland under Grant 2017/27/B/ST7/01874. Recommended by Associate Editor S. K. Spur-geon. (Corresponding author: Fangzhou Fu.) Dong Zhao is with the KIOS Research and Innovation Center of Excellence, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 1678, Cyprus (e-mail: zhao.dong@ucy.ac.cy). Publisher Copyright: {\textcopyright} 1963-2012 IEEE.",

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N1 - Funding Information: Manuscript received December 17, 2019; accepted March 29, 2020. Date of publication April 8, 2020; date of current version January 28, 2021. This work was supported in part by the National Natural Science Foundation of China under Grant 91948201, Grant 61973135, and Grant 61773242, in part by the Shandong Provincial Key Research and Development Program Major Scientific and Technological Innovation Project, China under Grant 2019JZZY010441, in part by the National Research Foundation of Korea grant funded by the Korea government (Ministry of Science and ICT) under Grant NRF-2020R1A2C1005449, and in part by the National Science Centre in Poland under Grant 2017/27/B/ST7/01874. Recommended by Associate Editor S. K. Spur-geon. (Corresponding author: Fangzhou Fu.) Dong Zhao is with the KIOS Research and Innovation Center of Excellence, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 1678, Cyprus (e-mail: zhao.dong@ucy.ac.cy). Publisher Copyright: © 1963-2012 IEEE.

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Fault Diagnosability Analysis of Two-Dimensional Linear Discrete Systems

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