Title :
Enhanced adaptive unscented Kalman filter for reaction wheels
Author :
Rahimi, Afshin ; Kumar, Krishna Dev ; Alighanbari, Hekmat
Author_Institution :
Dept. of Aerosp. Eng., Ryerson Univ., Toronto, ON, Canada
fDate :
4/1/2015 12:00:00 AM
Abstract :
This paper presents a methodology for improving the fault detection scheme of reaction wheels as actuators onboard satellites. An enhanced adaptive unscented Kalman filter (AUKF) is used, based on a generic adaptive Kalman filter combined with a particle swarm optimization for fault detection. Results show superior performance compared with a generic AUKF.
Keywords :
Kalman filters; actuators; artificial satellites; nonlinear filters; particle swarm optimisation; wheels; AUKF; actuators onboard satellites; enhanced adaptive unscented Kalman filter; fault detection scheme improvement; generic adaptive Kalman filter; particle swarm optimization; reaction wheels; Covariance matrices; Current measurement; Mathematical model; Noise; Noise measurement; Torque; Wheels;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2014.130766
