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
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;
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
Print_ISBN :
978-1-4799-3272-6
DOI :
10.1109/ACC.2014.6859292