DocumentCode :
2857784
Title :
Fault detection and diagnosis of an electrohydrostatic actuator using a novel interacting multiple model approach
Author :
Gadsden, S.A. ; McCullough, K. ; Habibi, S.R.
Author_Institution :
Dept. of Mech. Eng., McMaster Univ., Hamilton, ON, Canada
fYear :
2011
fDate :
June 29 2011-July 1 2011
Firstpage :
1396
Lastpage :
1401
Abstract :
In this paper, a new type of interacting multiple model (IMM) is introduced for the purposes of fault detection and diagnosis. The standard IMM is combined with a relatively new filtering method referred to as the smooth variable structure filter (SVSΓ). The SVSF is a type of sliding mode estimator, formulated in a predictor-correct fashion. It keeps the estimated state close to the true trajectory, and creates a stable estimation process. The combined method, referred to as the SVSF-IMM, is applied to an electrohydrostatic actuator (EHA). The results of the experiment are compared with the common form of the IMM, which utilizes the popular Kalman filter (KΓ).
Keywords :
Kalman filters; electric actuators; fault diagnosis; hydrostatics; variable structure systems; Kalman filter; SVSF-IMM; electrohydrostatic actuator; fault detection; fault diagnosis; filtering method; interacting multiple model approach; predictor-correct fashion; sliding mode estimator; smooth variable structure filter; stable estimation process; standard IMM; Actuators; Estimation; Fault detection; Friction; Mathematical model; Probability; Valves;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2011
Conference_Location :
San Francisco, CA
ISSN :
0743-1619
Print_ISBN :
978-1-4577-0080-4
Type :
conf
DOI :
10.1109/ACC.2011.5991440
Filename :
5991440
Link To Document :
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