Optimal Minimum-Variance Filtering for Systems with Unknown Inputs

Author

Hsieh, Chien-Shu

Author_Institution

Dept. of Electr. Eng., Ta Hwa Inst. of Technol., Hsinchu

Volume

1

fYear

0

fDate

0-0 0

Firstpage

1870

Lastpage

1874

Abstract

In this paper, the optimal minimum-variance filtering for systems with unknown inputs which affect both the system model and the measurements is addressed. A filtering performance degradation problem encountered in the optimal estimator filter proposed by Darouach et al. (2003) has been explored. The main problem encountered in the filter lies in the fact that the sufficient condition which guarantees the unbiasedness of the filter may exhibit restricted applications. A new optimal minimum-variance filter which compromises between the unbiasedness and the minimum-variance estimation has been proposed to remedy the problem. A numerical example is included in order to illustrate the proposed method

Keywords

filtering theory; filtering performance degradation; minimum-variance estimation; optimal minimum-variance filtering; Degradation; Electric variables measurement; Filtering algorithms; Finite impulse response filter; Kalman filters; Robustness; State estimation; Statistics; Sufficient conditions; Time varying systems; Minimum-variance filter; unbiased filter; unknown inputs estimation; unknown-input filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1712679

Filename

1712679