A bias-free least-squares parameter estimator for continuous-time state-space models

Author

Garnier, H. ; Sibille, P. ; Bastogne, T.

Author_Institution

CNRS, Univ. Henri Poincare, Vandoeuvre-les-Nancy, France

Volume

2

fYear

1997

fDate

10-12 Dec 1997

Firstpage

1860

Abstract

A bias-compensation method for continuous-time MIMO state-space model identification is presented. The Poisson moment functional approach is used to handle the time-derivative problem. The conventional least-squares algorithm, an instrumental variable algorithm and the proposed bias-free algorithm are applied to the parameter estimation of a simulated system under different noise levels via Monte Carlo simulations. The numerical study illustrates the performances of the proposed method

Keywords

MIMO systems; Monte Carlo methods; continuous time systems; least squares approximations; parameter estimation; state-space methods; Monte Carlo simulations; Poisson moment functional approach; bias-compensation method; bias-free least-squares parameter estimator; continuous-time MIMO state-space model; instrumental variable algorithm; time-derivative problem; Control system analysis; Design engineering; Differential equations; Instruments; MIMO; Noise level; Parameter estimation; State estimation; System analysis and design; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1997., Proceedings of the 36th IEEE Conference on

Conference_Location

San Diego, CA

ISSN

0191-2216

Print_ISBN

0-7803-4187-2

Type

conf

DOI

10.1109/CDC.1997.657854

Filename

657854