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Active fault diagnosis for stochastic large scale systems under non-separable costs

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43969687" target="_blank" >RIV/49777513:23520/24:43969687 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1016/j.automatica.2023.111348" target="_blank" >https://doi.org/10.1016/j.automatica.2023.111348</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.automatica.2023.111348" target="_blank" >10.1016/j.automatica.2023.111348</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Active fault diagnosis for stochastic large scale systems under non-separable costs

  • Original language description

    The paper focuses on active fault diagnosis of stochastic large-scale systems decomposed into several coupled subsystems, where the subsystem fault-free and faulty behavior is described in the multiple-model framework. In the active approach, the detector generates optimal excitation input to improve the diagnosis. This paper proposes a solution to the problems with cost functions in a generally non-separable form. Unlike the separable form, the generally non-separable form facilitates penalizing missed detections, false alerts, and incorrect, false identifications involving several subsystems simultaneously. Three approaches are proposed to treat such cost functions in the offline stage of the active fault diagnosis algorithm. Their performance is illustrated using a simple example and an elaborate example involving a power network system.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

    <a href="/en/project/GA22-11101S" target="_blank" >GA22-11101S: Tensor Decomposition in Active Fault Diagnosis for Stochastic Large Scale Systems</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Automatica

  • ISSN

    0005-1098

  • e-ISSN

    1873-2836

  • Volume of the periodical

    159

  • Issue of the periodical within the volume

    JAN 2024

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    9

  • Pages from-to

  • UT code for WoS article

    001102728500001

  • EID of the result in the Scopus database

    2-s2.0-85175268259