TY - GEN
T1 - Worst-case false alarm analysis of fault detection systems
AU - Hu, Bin
AU - Seiler Jr, Peter J
PY - 2014
Y1 - 2014
N2 - Model-based fault detection methods can be used to reduce the size, weight, and cost of safety-critical aerospace systems. However, the implementation of these methods is based on models. Therefore, disturbance and model uncertainty must be considered in order to certify the fault detection system. This paper considers the worst-case false alarm probability over a class of stochastic disturbances and model uncertainty. This is one analysis needed to assess the overall system reliability. The single step, worst-case false alarm probability is shown to be equivalent to a robust H2 analysis problem. Hence known results from the robust H2 literature can be used to upper bound this worst-case probability. Next, bounds are derived for the worst-case false alarm probability over multiple time steps. The multi-step analysis is important because reliability requirements for aerospace systems are typically specified over a time window, e.g. per hour. The bounds derived for the multi-step analysis account for the time correlations introduced by the system dynamics and fault detection filters. Finally, a numerical example is presented to demonstrate the proposed technique.
AB - Model-based fault detection methods can be used to reduce the size, weight, and cost of safety-critical aerospace systems. However, the implementation of these methods is based on models. Therefore, disturbance and model uncertainty must be considered in order to certify the fault detection system. This paper considers the worst-case false alarm probability over a class of stochastic disturbances and model uncertainty. This is one analysis needed to assess the overall system reliability. The single step, worst-case false alarm probability is shown to be equivalent to a robust H2 analysis problem. Hence known results from the robust H2 literature can be used to upper bound this worst-case probability. Next, bounds are derived for the worst-case false alarm probability over multiple time steps. The multi-step analysis is important because reliability requirements for aerospace systems are typically specified over a time window, e.g. per hour. The bounds derived for the multi-step analysis account for the time correlations introduced by the system dynamics and fault detection filters. Finally, a numerical example is presented to demonstrate the proposed technique.
KW - Aerospace
KW - Fault detection/accomodation
KW - Stochastic systems
UR - http://www.scopus.com/inward/record.url?scp=84905714237&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84905714237&partnerID=8YFLogxK
U2 - 10.1109/ACC.2014.6859292
DO - 10.1109/ACC.2014.6859292
M3 - Conference contribution
AN - SCOPUS:84905714237
SN - 9781479932726
T3 - Proceedings of the American Control Conference
SP - 654
EP - 659
BT - 2014 American Control Conference, ACC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 American Control Conference, ACC 2014
Y2 - 4 June 2014 through 6 June 2014
ER -