POLYFILTER: A new state estimation filter for nonlinear systems

Author

Sadati, Nasser ; Ghaffarkhah, Alireza

Author_Institution

Sharif Univ. of Tech., Tehran

fYear

2007

fDate

17-20 Oct. 2007

Firstpage

2643

Lastpage

2647

Abstract

In this paper, we propose a new state estimation filter called POLYFILTER, which is based on polynomial approximation of the nonlinear transformation obtained using particular multidimensional extension of Stirling´s Interpolation Formula (SIF). In contrast to the Extended Kalman Filtering, no derivatives are needed in the interpolation formula; only function evaluations are needed during interpolation. This accommodates easy implementation of the filter, and it enables the state estimation even when there are singular points in which the derivatives are undefined.

Keywords

Kalman filters; filtering theory; nonlinear filters; polynomial approximation; POLYFILTER; Stirling interpolation formula; extended Kalman filtering; multidimensional extension; nonlinear systems; nonlinear transformation; polynomial approximation; state estimation filter; Automatic control; Electronic mail; Filtering; Interpolation; Kalman filters; Multidimensional systems; Nonlinear control systems; Nonlinear systems; Polynomials; State estimation; Derivative-free state estimation; Kalman filter; Nonlinear systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Automation and Systems, 2007. ICCAS '07. International Conference on

Conference_Location

Seoul

Print_ISBN

978-89-950038-6-2

Electronic_ISBN

978-89-950038-6-2

Type

conf

DOI

10.1109/ICCAS.2007.4406814

Filename

4406814