Adaptive Fading Kalman Filter with Q-adaptation for estimation of AUV dynamics

Hacızade C., Vural S. Y., Hajiyeva U.

2012 20th Mediterranean Conference on Control and Automation, MED 2012, Barcelona, Spain, 3 - 06 July 2012, pp.697-702 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/med.2012.6265719
  • City: Barcelona
  • Country: Spain
  • Page Numbers: pp.697-702
  • Istanbul Technical University Affiliated: Yes


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. © 2012 IEEE.