Multivariable least squares frequency domain identification using polynomial matrix fraction descriptions

Author

de Callafon, R.A. ; de Roover, D. ; Den Hof, P. M J Van

Author_Institution

Mech. Eng. Syst. & Control Group, Delft Univ. of Technol., Netherlands

Volume

2

fYear

1996

fDate

11-13 Dec 1996

Firstpage

2030

Abstract

In this paper an approach is presented to estimate a linear multivariable model on the basis of (noisy) frequency domain data via a curve fitting procedure. The multivariable model is parametrized in either a left or a right polynomial matrix fraction description and the parameters are computed by using a two-norm minimization of a multivariable output error. Additionally, input-output or element-wise based multivariable frequency weightings can be specified to tune the curve fitting error in a flexible way. The procedure is demonstrated on experimental data obtained from a 3 input 3 output wafer stepper system

Keywords

curve fitting; electronic equipment manufacture; frequency response; identification; least squares approximations; linear systems; minimisation; multivariable control systems; polynomial matrices; position control; 3 input 3 output wafer stepper system; curve fitting; element-wise based multivariable frequency weightings; frequency domain data; input-output based multivariable frequency weightings; linear multivariable model; multivariable least squares frequency domain identification; multivariable output error; polynomial matrix fraction descriptions; two-norm minimization; Control systems; Curve fitting; Frequency domain analysis; Frequency estimation; Least squares methods; Mechanical engineering; Noise reduction; Polynomials; Semiconductor device modeling; Test equipment;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1996., Proceedings of the 35th IEEE Conference on

Conference_Location

Kobe

ISSN

0191-2216

Print_ISBN

0-7803-3590-2

Type

conf

DOI

10.1109/CDC.1996.572883

Filename

572883