• DocumentCode
    2620651
  • Title

    Diagnosability of stochastic automata

  • Author

    Thorsley, David ; Teneketzis, Demosthenis

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
  • Volume
    6
  • fYear
    2003
  • fDate
    9-12 Dec. 2003
  • Firstpage
    6289
  • Abstract
    A methodology for diagnosability of finite-state stochastic automata is established in this paper. Two notions of diagnosability for stochastic automata are defined, and a stochastic analogue of the logical diagnoser is constructed. The stochastic diagnoser is used to (i) specify off-line conditions sufficient to guarantee these notions of diagnosability; and (ii) determine how to perform on-line diagnosis of failure events.
  • Keywords
    discrete event systems; fault diagnosis; large-scale systems; stochastic automata; diagnosability; discrete event system; failure diagnosis; finite-state stochastic automata; offline condition specifications; online events failure diagnosis; stochastic diagnoser; Automata; Event detection; Fault detection; Fault diagnosis; Fault trees; Intelligent sensors; Sensor systems; State-space methods; Stochastic processes; Stochastic systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-7924-1
  • Type

    conf

  • DOI
    10.1109/CDC.2003.1272304
  • Filename
    1272304