Article

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

CRAN, CNRS, Cosnes et Romain
IEEE Transactions on Automatic Control (impact factor: 2.11). 05/1997; DOI:10.1109/9.566674 pp.581 - 586
Source: IEEE Xplore

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

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Keywords

arbitrary matrix
 
convergence
 
convergence analysis
 
first-order linearization technique
 
local asymptotic convergence
 
modified EKF
 
new formulation
 
nonlinear discrete-time systems
 
nonlinear identification problem
 
sufficient conditions