Receding-horizon unbiased FIR filters for continuous-time state-space models without a priori initial state information

Author

Han, Soo Hee ; Kwon, Wook Hyun ; Kim, Pyung Soo

Author_Institution

Eng. Res. Center for Adv. Control & Instrum., Seoul Nat. Univ., South Korea

Volume

46

Issue

5

fYear

2001

fDate

5/1/2001 12:00:00 AM

Firstpage

766

Lastpage

770

Abstract

A receding horizon unbiased finite-impulse response filter (RHUFF) is proposed for continuous-time state space models. Linearity, unbiasedness, finite-impulse response (FIR) structure, and independence of the initial state information will be required in advance, in addition to a performance index of minimum variance. The proposed RHUFF is obtained by directly minimizing the performance index with the unbiasedness constraint. The proposed RHUFF is represented first in a standard FIR form and then in an iterative form. It is shown that the RHUFF is equivalent to the existing receding horizon (RH) Kalman FIR filter. The former is more systematic and logical, while the latter is heuristic due to the handling of infinite covariance of the initial state information

Keywords

FIR filters; continuous time systems; performance index; state estimation; state-space methods; continuous-time state-space models; infinite covariance; receding-horizon unbiased FIR filters; unbiasedness constraint; Finite impulse response filter; IIR filters; Information filtering; Information filters; Kalman filters; Linearity; Nonlinear filters; Performance analysis; State estimation; State-space methods;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.920798

Filename

920798