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Diagnosability of unambiguous max-plus automata

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    SYSNO ASEP0562936
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleDiagnosability of unambiguous max-plus automata
    Author(s) Lai, A. (CN)
    Komenda, Jan (MU-W) RID, SAI, ORCID
    Lahaye, S. (FR)
    Source TitleIEEE Transactions on Systems Man Cybernetics-Systems . - : Institute of Electrical and Electronics Engineers - ISSN 2168-2216
    Roč. 52, č. 11 (2022), s. 7302-7311
    Number of pages10 s.
    Languageeng - English
    CountryUS - United States
    Keywordsfault diagnosis ; discrete-event systems ; max-plus automata
    Subject RIVBA - General Mathematics
    OECD categoryAutomation and control systems
    R&D ProjectsGC19-06175J GA ČR - Czech Science Foundation (CSF)
    Method of publishingLimited access
    Institutional supportMU-W - RVO:67985840
    UT WOS000800807100001
    EID SCOPUS85140292651
    DOI10.1109/TSMC.2022.3176045
    AnnotationThis article investigates diagnosability and T-diagnosability for discrete-event systems modeled by unambiguous max-plus automata (UMPAs). More precisely, diagnosability requires that the occurrence of any fault can be detected within a finite number of events after the fault has occurred. T-diagnosability requires that the occurrence of any fault can be detected within a delay of at most T time units after its occurrence. First, we propose a polynomial-time algorithm based on the construction of a nondeterministic finite automaton over a weighted alphabet for diagnosability verification of a UMPA. Second, we prove that T-diagnosability of a UMPA can be studied by reducing it to the problem of diagnosability. Third, we introduce an approach to calculate the upper on the time needed for detecting fault occurrence for a diagnosable UMPA, and its complexity is of sixth order in the number of states of the UMPA.
    WorkplaceMathematical Institute
    ContactJarmila Štruncová, struncova@math.cas.cz, library@math.cas.cz, Tel.: 222 090 757
    Year of Publishing2023
    Electronic addresshttps://doi.org/10.1109/TSMC.2022.3176045
Number of the records: 1  

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