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@inproceedings{Boem:2016:10.1109/CDC.2016.7798443,
author = {Boem, F and Carli, R and Farina, M and Ferrari-Trecate, G and Parisini, T},
doi = {10.1109/CDC.2016.7798443},
publisher = {IEEE},
title = {Scalable monitoring of interconnected stochastic systems},
url = {http://dx.doi.org/10.1109/CDC.2016.7798443},
year = {2016}
}

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TY  - CPAPER
AB  - In this paper, we propose a novel distributed faultdetection  method  to  monitor  the  state  of  a  linear  system,  par-titioned  into  interconnected  subsystems.  The  approach  hingeson  the  definition  of  a  partition-based  distributed  Luenbergerestimator,  based  on  the  local  model  of  the  subsystems  andthat  takes  into  account  the  dynamic  coupling  terms  betweenthe  subsystems.  The  proposed  methodology  computes  –in adistributed way– a bound on the variance of a properly definedresidual   signal,   considering   the   uncertainty   related   to   thestate estimates performed by the neighboring subsystems. Thisbound allows the computation of suitable local thresholds withguaranteed  maximum  false-alarms  rate.  The  implementationof   the   proposed   estimation   and   fault   detection   method   isscalable,  allowingPlug & Playoperations  and  the  possibilityto  disconnect  the  faulty  subsystem  after  fault  detection.  Theo-retical conditions guaranteeing the convergence of the estimatesand  of  the  bounds  are  provided.  Simulation  results  show  theeffectiveness  of  the  proposed  method.
AU  - Boem,F
AU  - Carli,R
AU  - Farina,M
AU  - Ferrari-Trecate,G
AU  - Parisini,T
DO  - 10.1109/CDC.2016.7798443
PB  - IEEE
PY  - 2016///
TI  - Scalable monitoring of interconnected stochastic systems
UR  - http://dx.doi.org/10.1109/CDC.2016.7798443
UR  - http://hdl.handle.net/10044/1/43605
ER  -

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