A subspace approach for approximation of rational matrix functions to sampled data

Author

McKelvey, Tomas ; Helmersson, Anders

Author_Institution

Dept. of Electr. Eng., Linkoping Univ., Sweden

Volume

4

fYear

1996

fDate

11-13 Dec 1996

Firstpage

3660

Abstract

Algorithms for approximation of rational matrix factors to data is described. The method is based on a subspace based multivariable frequency domain state-space identification, canonical and spectral factorization and parametric optimization. The algorithms can be used for identifying spectral factors and factors of positive real functions from frequency data. The methods are directly applicable in the D-K algorithm for complex μ-synthesis and the Y-Z-K algorithm for mixed μ-synthesis

Keywords

control system synthesis; frequency-domain analysis; function approximation; identification; matrix decomposition; multivariable systems; optimisation; sampled data systems; state-space methods; D-K algorithm; Y-Z-K algorithm; canonical factorization; complex μ-synthesis; frequency data; mixed μ-synthesis; parametric optimization; positive real functions; rational matrix function approximation; sampled data; spectral factorization; subspace approach; subspace-based multivariable frequency-domain state-space identification; Approximation algorithms; Automatic control; Councils; Data engineering; Filtering; Frequency domain analysis; Optimization methods; Robust control; Signal processing; Signal processing algorithms;

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.1996.577197

Filename

577197