Title :
Diagnosability of stochastic automata
Author :
Thorsley, David ; Teneketzis, Demosthenis
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
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;
Conference_Titel :
Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
Print_ISBN :
0-7803-7924-1
DOI :
10.1109/CDC.2003.1272304
