TY - GEN
T1 - Sensor fault detection by testing the largest eigenvalue of the innovation covariance using Tracy-Widom distribution
AU - Hajiyev, Ch
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=77957795806&partnerID=8YFLogxK
U2 - 10.1109/acc.2010.5530786
DO - 10.1109/acc.2010.5530786
M3 - Conference contribution
AN - SCOPUS:77957795806
SN - 9781424474264
T3 - Proceedings of the 2010 American Control Conference, ACC 2010
SP - 5427
EP - 5432
BT - Proceedings of the 2010 American Control Conference, ACC 2010
PB - IEEE Computer Society
ER -