TY - GEN
T1 - Adaptive Fading Kalman Filter with Q-adaptation for estimation of AUV dynamics
AU - Hajiyev, Chingiz
AU - Vural, S. Yenal
AU - Hajiyeva, Ulviyya
PY - 2012
Y1 - 2012
N2 - This article is basically focused on application of the Robust Kalman Filter (RKF) algorithm to the estimation of high speed an autonomous underwater vehicle (AUV) dynamics. In the normal operation conditions of AUV, conventional Kalman filter gives sufficiently good estimation results. However, if any kind of malfunction occurs in the system, KF gives inaccurate results and diverges by time. This study, introduces Adaptive Fading Kalman Filter (AFKF) algorithm with the filter gain correction for the case of system malfunctions. By the use of defined variables named as single and multiple fading factors, the estimations are corrected without affecting the characteristic of the accurate ones.
AB - This article is basically focused on application of the Robust Kalman Filter (RKF) algorithm to the estimation of high speed an autonomous underwater vehicle (AUV) dynamics. In the normal operation conditions of AUV, conventional Kalman filter gives sufficiently good estimation results. However, if any kind of malfunction occurs in the system, KF gives inaccurate results and diverges by time. This study, introduces Adaptive Fading Kalman Filter (AFKF) algorithm with the filter gain correction for the case of system malfunctions. By the use of defined variables named as single and multiple fading factors, the estimations are corrected without affecting the characteristic of the accurate ones.
UR - https://www.scopus.com/pages/publications/84866933792
U2 - 10.1109/MED.2012.6265719
DO - 10.1109/MED.2012.6265719
M3 - Conference contribution
AN - SCOPUS:84866933792
SN - 9781467325318
T3 - 2012 20th Mediterranean Conference on Control and Automation, MED 2012 - Conference Proceedings
SP - 697
EP - 702
BT - 2012 20th Mediterranean Conference on Control and Automation, MED 2012 - Conference Proceedings
T2 - 2012 20th Mediterranean Conference on Control and Automation, MED 2012
Y2 - 3 July 2012 through 6 July 2012
ER -