Title :
Least order fault and model detection using multi-models
Author_Institution :
German Aerospace Center (DLR), Germany
Abstract :
Multi-model based fault detection is often a viable alternative to various multi-model based state estimation techniques using banks of Kalman filters. A main advantage of the fault detection techniques based approach is the possibility to use detectors having low order dynamics with disturbance decoupling capabilities. The proposed synthesis algorithm of detectors relies on numerically reliable rational nullspace techniques enhanced with optimal tuning of detection sensitivities. The applicability of the multi-model based approach to solve fault identification problems is illustrated by solving a flight actuator fault detection problem with simultaneous faults.
Keywords :
Kalman filters; fault diagnosis; identification; sensors; state estimation; Kalman filters; detection sensitivities; disturbance decoupling capabilities; fault identification problems; flight actuator fault detection problem; least order fault detection; model detection; multimodels; numerically reliable rational nullspace techniques; optimal tuning; state estimation techniques; Actuators; Detectors; Fault detection; Fault diagnosis; Fault tolerance; Filters; Frequency; Signal processing; Signal synthesis; State estimation;
Conference_Titel :
Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3871-6
Electronic_ISBN :
0191-2216
DOI :
10.1109/CDC.2009.5400784