Title :
Set-membership identification and fault detection using a bayesian framework
Author :
Fernandez-Canti, Rosa M. ; Blesa, J. ; Puig, Vicenc
Author_Institution :
Signal Theor. &Jordi Girona 1-3, Commun. Dept. (TSC), Tech. Univ. of Catalonia (UPC), Barcelona, Spain
Abstract :
This paper deals with the problem of set-membership identification and fault detection using a Bayesian framework. The paper presents how the set-membership model estimation problem can be reformulated from a Bayesian viewpoint in order to determine the feasible parameter set and, in a posterior fault detection stage, to check the consistency between data and the model. The paper shows that, assuming uniform distributed measurement noise and flat model prior probability distribution, the Bayesian approach leads to the same feasible parameter set than the set-membership strips technique and, additionally, can deal with models nonlinear in the parameters. The procedure and results are illustrated by means of the application to a quadruple tank process.
Keywords :
Bayes methods; fault diagnosis; identification; modelling; statistical distributions; Bayesian framework; Bayesian viewpoint; distributed measurement noise; fault detection; flat model prior probability distribution; quadruple tank process; set membership identification; set membership model estimation problem; set membership strips; Approximation methods; Bayes methods; Data models; Fault detection; Strips; Uncertainty; Vectors;
Conference_Titel :
Control and Fault-Tolerant Systems (SysTol), 2013 Conference on
Conference_Location :
Nice
DOI :
10.1109/SysTol.2013.6693825