DocumentCode
3281750
Title
Sensor fault detection by testing the largest eigenvalue of the innovation covariance using Tracy-Widom distribution
Author
Hajiyev, Ch
Author_Institution
Fac. of Aeronaut. & Astronaut., Istanbul Tech. Univ., Istanbul, Turkey
fYear
2010
fDate
June 30 2010-July 2 2010
Firstpage
5427
Lastpage
5432
Abstract
Operative method of testing the innovation covariance of the Kalman filter is proposed. The maximal eigenvalue of the random Wishart matrix is used in this process as monitoring statistic, and the testing problem is reduced to determine the asymptotics for largest eigenvalue of the Wishart matrix. As a result, algorithm for testing the innovation covariance based on Tracy-Widom distribution is proposed. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of pitch rate gyro, air speed indicator and angle of attack sensor failures, which affect the innovation covariance, are examined.
Keywords
Kalman filters; covariance analysis; eigenvalues and eigenfunctions; fault diagnosis; sensors; statistical distributions; F-16 aircraft model; Kalman filter; Tracy Widom distribution; air speed indicator; eigenvalue; innovation covariance; pitch rate gyro; random Wishart matrix; sensor fault detection; Actuators; Aerospace control; Aircraft; Covariance matrix; Eigenvalues and eigenfunctions; Fault detection; Noise measurement; Statistical analysis; Technological innovation; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2010
Conference_Location
Baltimore, MD
ISSN
0743-1619
Print_ISBN
978-1-4244-7426-4
Type
conf
DOI
10.1109/ACC.2010.5530786
Filename
5530786
Link To Document