• DocumentCode
    2382808
  • Title

    Diagnosability of stochastic discrete-event systems under unreliable observations

  • Author

    Thorsley, David ; Yoo, Tae-Sic ; Garcia, Humberto E.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Washington, Seattle, WA
  • fYear
    2008
  • fDate
    11-13 June 2008
  • Firstpage
    1158
  • Lastpage
    1165
  • Abstract
    We investigate diagnosability of stochastic discrete-event systems where the observation of certain events is unreliable, that is, there are non-zero probabilities of the misdetection and misclassification of events based on faulty sensor readings. Such sensor unreliability is unavoidable in applications such as nuclear energy generation. We propose the notions of uA- and uAA-diagnosability for stochastic automata and demonstrate their relationship with the concepts of A- and AA-diagnosabilty defined previously. We extend the concept of the stochastic diagnoser to the unreliable observation paradigm and find conditions for uA- and uAA-diagnosability.
  • Keywords
    discrete event systems; nuclear power; observability; state estimation; stochastic automata; nuclear energy generation; stochastic automata; stochastic diagnoser; stochastic discrete-event systems; uA-diagnosability; uAA-diagnosability; Automata; Control systems; Discrete event systems; Nuclear power generation; Power system modeling; Power system reliability; Safety; Sensor systems; Stochastic processes; Stochastic systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2008
  • Conference_Location
    Seattle, WA
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4244-2078-0
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2008.4586649
  • Filename
    4586649