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
Link To Document :
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