Robust rational approximation for identification

Author

Bultheel, A. ; Van Barel, M. ; Rolain, Y. ; Schoukens, J.

Author_Institution

Dept. of Comput. Sci., Katholieke Univ., Leuven, Belgium

Volume

5

fYear

2001

fDate

2001

Firstpage

4770

Abstract

Using vector orthogonal polynomials as basis functions for the maximum-likelihood (ML) frequency domain identification of the rational form of a linear time invariant system is shown to circumvent all the well known numerical conditioning problems. For identification of very high order systems (e.g. 100/100), systems that operate over a wide frequency band, or even in the presence of over- and undermodelling, condition numbers of less than 10 are reported on real measurements and simulation

Keywords

least squares approximations; linear systems; maximum likelihood estimation; poles and zeros; polynomials; basis functions; condition numbers; linear time invariant system; maximum-likelihood frequency domain identification; numerical conditioning problems; over-modelling; rational form; robust rational approximation; under-modelling; vector orthogonal polynomials; very high order systems; Cost function; Equations; Frequency domain analysis; Frequency estimation; Frequency measurement; Frequency response; Least squares methods; MIMO; Polynomials; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2001. Proceedings of the 40th IEEE Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-7061-9

Type

conf

DOI

10.1109/.2001.980961

Filename

980961