Convergence analysis of the extended Kalman filter used as an observer for nonlinear deterministic discrete-time systems

Author

Boutayeb, M. ; Rafaralahy, H. ; Darouach, M.

Author_Institution

CRAN, CNRS, Cosnes et Romain, France

Volume

42

Issue

4

fYear

1997

fDate

4/1/1997 12:00:00 AM

Firstpage

581

Lastpage

586

Abstract

In this paper, convergence analysis of the extended Kalman filter (EKF), when used as an observer for nonlinear deterministic discrete-time systems, is presented. Based on a new formulation of the first-order linearization technique, sufficient conditions to ensure local asymptotic convergence are established. Furthermore, it is shown that the design of the arbitrary matrix plays an important role in enlarging the domain of attraction and then improving the convergence of the modified EKF significantly. The efficiency of this approach, compared to the classical version of the EKF, is shown through a nonlinear identification problem as well as a state and parameter estimation of nonlinear discrete-time systems

Keywords

Kalman filters; convergence; discrete time systems; filtering theory; linearisation techniques; nonlinear systems; observers; parameter estimation; EKF; attraction domain; convergence analysis; extended Kalman filter; first-order linearization technique; local asymptotic convergence; nonlinear deterministic discrete-time systems; observer; parameter estimation; state estimation; Convergence; Filters; Linearization techniques; Nonlinear equations; Nonlinear systems; Observability; Parameter estimation; Riccati equations; State estimation; Sufficient conditions;

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/9.566674

Filename

566674