Title :
Optimal filtering with unknown inputs and reduced-order Kalman filter
Author :
Keller, J.Y. ; Darouach, M.
Author_Institution :
CRAN, Univ. de Nancy I, Nancy, France
Abstract :
This paper presents a new reduced-order Kalman filter for discrete-time dynamic stochastic linear systems to estimate a part of the state when all the measurements are affected by noises. The noninteresting part of the state is treated as an unknown input not constrained to evolve in accordance with a dynamic equation.
Keywords :
Kalman filters; discrete time filters; state estimation; stochastic processes; discrete-time dynamic stochastic linear systems; dynamic equation; optimal filtering; reduced-order Kalman filter; state estimation; unknown input; unknown inputs; Kalman filters; Mathematical model; Noise; Noise measurement; Observers; Stochastic systems; State estimation; reduced-order filter; stochastic system; unknown input;
Conference_Titel :
Control Conference (ECC), 1997 European
Conference_Location :
Brussels
Print_ISBN :
978-3-9524269-0-6
