Title :
Diagnosability of stochastic discrete-event systems
Author :
Thorsley, David ; Teneketzis, Demosthenis
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Michigan, Ann Arbor, MI, USA
fDate :
4/1/2005 12:00:00 AM
Abstract :
We investigate diagnosability of stochastic discrete-event systems. We define the notions of A- and AA-diagnosability for stochastic automata; these notions are weaker than the corresponding notion of diagnosability for logical automata introduced by Sampath et al. Through the construction of a stochastic diagnoser, we determine offline conditions necessary and sufficient to guarantee A-diagnosability and sufficient to guarantee AA-diagnosability. We also show how the stochastic diagnoser can be used for on-line diagnosis of failure events. We illustrate the results through two examples from HVAC systems.
Keywords :
discrete event systems; fault diagnosis; stochastic automata; stochastic systems; A-diagnosability; AA-diagnosability; HVAC systems; failure detection; fault diagnosis; stochastic automata; stochastic discrete-event systems diagnosability; Automata; Context modeling; Delay; Discrete event systems; Event detection; Fault detection; Fault diagnosis; Sensor systems; Stochastic processes; Stochastic systems; Discrete-event systems; failure detection; fault diagnosis; probabilistic models; stochastic automata;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2005.844722
