A linearization free recursive prediction error method for combined state and parameter estimation for nonlinear systems

Author

Qi Zhao ; Bohn, Christian

Author_Institution

Inst. for Electr. Inf. Tech., Clausthal Univ. of Technol., Clausthal-Zellerfeld, Germany

fYear

2013

fDate

17-19 June 2013

Firstpage

899

Lastpage

904

Abstract

A novel method for combined state and parameter estimation is presented. The method is based on the recursive prediction error method for nonlinear system and is able to estimate states and parameters from nonlinear state-space models simultaneously. Moreover, because of the application of the deterministic sampling approach, no model linearization is required. A simple example (real-time parameter estimation for a three-tank system) is included to demonstrate the performance of the algorithm.

Keywords

deterministic algorithms; error analysis; nonlinear systems; parameter estimation; recursive estimation; sampling methods; state estimation; state-space methods; deterministic sampling approach; linearization free recursive prediction error method; nonlinear systems; real-time parameter estimation; state estimation; state-space models; three-tank system; Adaptation models; Covariance matrices; Equations; Mathematical model; Noise; Sensitivity; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference (ACC), 2013

Conference_Location

Washington, DC

ISSN

0743-1619

Print_ISBN

978-1-4799-0177-7

Type

conf

DOI

10.1109/ACC.2013.6579950

Filename

6579950