Title :
Robust two-stage Kalman filters for systems with unknown inputs
Author :
Hsieh, Chien-Shu
Author_Institution :
Mech. Ind. Res. Labs., Ind. Technol. Res. Inst., Hsinchu, Taiwan
fDate :
12/1/2000 12:00:00 AM
Abstract :
A method is developed for the state estimation of linear time-varying discrete systems with unknown inputs. By making use of the two-stage Kalman filtering technique and a proposed unknown inputs filtering technique, a robust two-stage Kalman filter which is unaffected by the unknown inputs can be readily derived and serves as an alternative to the Kitanidis´ (1987) unbiased minimum-variance filter. The application of this new filter is illustrated by optimal filtering for systems with unknown inputs
Keywords :
Kalman filters; discrete systems; filtering theory; linear systems; state estimation; stochastic systems; time-varying systems; uncertain systems; linear time-varying discrete systems; optimal filtering; robust two-stage Kalman filters; unknown inputs filtering technique; Adaptive filters; Covariance matrix; Filtering; Kalman filters; Lagrangian functions; Noise measurement; Robustness; State estimation; Stochastic processes; Time varying systems;
Journal_Title :
Automatic Control, IEEE Transactions on