Title :
Sensor fusion based on fuzzy Kalman filter
Author :
Sasiadek, J.Z. ; Khe, J.
Abstract :
We present a fuzzy Kalman filter, which is based on fuzzy logic theory and a Kalman filter. It is similar to a Kalman filter when a linear system with Gaussian noise is considered. However, when non-Gaussian noise is introduced, it is shown that the fuzzy Kalman filter outperforms the Kalman filter and the Kalman filter does not work well. We demonstrate the performances of the Kalman filter and the fuzzy Kalman filter for a position estimation application under different circumstances. Comparisons are made to draw conclusions
Keywords :
Kalman filters; aerospace control; covariance matrices; fuzzy control; fuzzy logic; fuzzy set theory; noise; position control; sensor fusion; space vehicles; state estimation; fuzzy Kalman filter; fuzzy logic control; fuzzy logic theory; nonGaussian noise; sensor fusion; Covariance matrix; Equations; Error correction; Filters; Fuzzy control; Fuzzy logic; Motion control; Sensor fusion; State estimation; Time measurement;
Conference_Titel :
Robot Motion and Control, 2001 Proceedings of the Second International Workshop on
Conference_Location :
Bukowy Dworek
Print_ISBN :
83-7143-515-0
DOI :
10.1109/ROMOCO.2001.973467