Sensor location for diagnosis in linear systems : A structural approach - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Automatic Control Année : 2007

Sensor location for diagnosis in linear systems : A structural approach

Résumé

We consider here the Fault Detection and Isolation (FDI) problem for linear systems. We are interested in designing a set of observer-based residuals, in such a way that the transfer from the faults to the residuals is diagonal and the transfer from the disturbances to the residuals is zero. We deal with this problem when the system under consideration is structured, that is, the entries of the system matrices are either fixed zeros or free parameters. This problem can be solved in terms of the graph that can be associated in a natural way with a structured system. When the FDI solvability conditions are not satisfied, we assume that internal variables can be measured at a cost and look into the question of wether the problem is solvable with these new measurements. We give solvability conditions for a solution with a minimal number of additional sensors and among such solutions provide a minimal cost solution for the sensor location problem under consideration. We pay particular attention to the internal analysis of the system, and we propose a structural decomposition of the system associated graph based on some particular separators. This analysis leads to the definition of a reduced system. We prove that some potential additional sensors are inefficient for solving our FDI problem and that the FDI problem can be solved using only measurements on the reduced system.
Fichier non déposé

Dates et versions

hal-00130619 , version 1 (13-02-2007)

Identifiants

Citer

Christian Commault, Jean-Michel Dion. Sensor location for diagnosis in linear systems : A structural approach. IEEE Transactions on Automatic Control, 2007, 52 (2), pp.155-169. ⟨10.1109/TAC.2006.889865⟩. ⟨hal-00130619⟩
80 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More