TY - GEN
T1 - Bayesian inference for fault-tolerant control
AU - Villez, Kris
AU - Venkatasubramanian, Venkat
AU - Narasimhan, Shankar
PY - 2009
Y1 - 2009
N2 - In this contribution, we present initial developments in view of model-based fault-tolerant control (FTC). In this context, we use an original method based on the Kalman-filter by which fault detection, diagnosis and accommodation is possible provided that an accurate model is available. Since this is not generally true, we attempt to alleviate this necessity by means of accounting for uncertainty, in both model as well as in the measurements used for fault diagnosis. Our preliminary results are focused on the diagnosis step in the FTC scheme.
AB - In this contribution, we present initial developments in view of model-based fault-tolerant control (FTC). In this context, we use an original method based on the Kalman-filter by which fault detection, diagnosis and accommodation is possible provided that an accurate model is available. Since this is not generally true, we attempt to alleviate this necessity by means of accounting for uncertainty, in both model as well as in the measurements used for fault diagnosis. Our preliminary results are focused on the diagnosis step in the FTC scheme.
KW - Bayesian inference
KW - Fault detection and diagnosis
KW - Fault tolerant control
KW - Kalman filter
UR - http://www.scopus.com/inward/record.url?scp=70449394555&partnerID=8YFLogxK
U2 - 10.1109/ISRCS.2009.5251340
DO - 10.1109/ISRCS.2009.5251340
M3 - Conference contribution
AN - SCOPUS:70449394555
SN - 9781424448548
T3 - Proceedings - ISRCS 2009 - 2nd International Symposium on Resilient Control Systems
SP - 51
EP - 53
BT - Proceedings - ISRCS 2009 - 2nd International Symposium on Resilient Control Systems
T2 - ISRCS 2009 - 2nd International Symposium on Resilient Control Systems
Y2 - 11 August 2009 through 13 August 2009
ER -