Robust state estimator of stochastic linear systems with unknown disturbances

Author

Kim, J.-H. ; Oh, J.H.

Author_Institution

Dept. of Mech. Eng., Korea Adv. Inst. of Sci. & Technol., Seoul, South Korea

Volume

147

Issue

2

fYear

2000

fDate

3/1/2000 12:00:00 AM

Firstpage

224

Lastpage

228

Abstract

The design of a filtering algorithm when an unknown disturbance exists is described. An alternative method to solve the disturbance estimation problem is proposed, which is to reformulate it to a tracking problem by using the relation of the filter update. The reformulation of the problem makes it possible to use an effective sliding surface and fast estimate against arbitrary disturbance. A disturbance estimator using the discrete sliding mode is designed and improved by introducing a prediction parameter. In addition, a disturbance detection algorithm having a moderate calculation cost is designed using filter update and innovations. The normalised testing parameter makes it possible to use the standard chi-square table to determine the threshold level. The stability of the suggested algorithm is given and simulation results are included to demonstrate the effectiveness of the proposed technique

Keywords

Kalman filters; discrete systems; filtering theory; linear systems; prediction theory; state estimation; stochastic systems; uncertain systems; variable structure systems; discrete sliding mode; disturbance detection algorithm; disturbance estimation; disturbance estimator; filter update; filtering algorithm; innovations; normalised testing parameter; prediction parameter; robust state estimator; sliding surface; standard chi-square table; stochastic linear systems; threshold level; tracking problem; unknown disturbances;

fLanguage

English

Journal_Title

Control Theory and Applications, IEE Proceedings -

Publisher

iet

ISSN

1350-2379

Type

jour

DOI

10.1049/ip-cta:20000174

Filename

843261