DocumentCode
184801
Title
Worst-case false alarm analysis of fault detection systems
Author
Bin Hu ; Seiler, Patrick
Author_Institution
Aerosp. Eng. & Mech. Dept., Univ. of Minnesota, Minneapolis, MN, USA
fYear
2014
fDate
4-6 June 2014
Firstpage
654
Lastpage
659
Abstract
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.
Keywords
H∞ control; Monte Carlo methods; aerospace control; fault diagnosis; fault tolerant control; safety systems; fault detection systems; model uncertainty; model-based fault detection methods; reliability requirements; robust H2 analysis problem; safety-critical aerospace systems; stochastic disturbance; time correlations; worst-case false alarm analysis; worst-case false alarm probability; Aircraft; Atmospheric modeling; Fault detection; Mathematical model; Robustness; Uncertainty; Upper bound; Aerospace; Fault detection/accomodation; Stochastic systems;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2014
Conference_Location
Portland, OR
ISSN
0743-1619
Print_ISBN
978-1-4799-3272-6
Type
conf
DOI
10.1109/ACC.2014.6859292
Filename
6859292
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