Identification of linear systems in the presence of nonlinear distortions. A frequency domain approach. II. Parametric identification

Author

Schoukens, J. ; Dobrowiecki, Tadeusz ; Pintelon, R.

Author_Institution

Dept. ELEC, Vrije Univ., Brussels, Belgium

Volume

2

fYear

1995

fDate

13-15 Dec 1995

Firstpage

1222

Abstract

For pt. I see ibid., p. 1216-21 (1995). This paper concerns the asymptotic behaviour of parametric frequency-domain identification methods to model linear dynamic systems in the presence of nonlinear distortions, using random multisine excitations. Consistency is shown with respect to the general conditions. A function of dependency is defined to detect the presence of unmodelled dynamics, nonlinear distortions and to bound the bias error on the transfer function estimate

Keywords

frequency-domain analysis; identification; nonlinear systems; transfer functions; asymptotic behaviour; bounded bias error; linear dynamic systems; linear systems identification; nonlinear distortions; parametric frequency-domain identification; random multisine excitations; transfer function estimate; unmodelled dynamics detection; Distortion measurement; Frequency domain analysis; Government; Instruments; Linear systems; Noise measurement; Nonlinear distortion; Nonlinear dynamical systems; Testing; Transfer functions;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1995., Proceedings of the 34th IEEE Conference on

Conference_Location

New Orleans, LA

ISSN

0191-2216

Print_ISBN

0-7803-2685-7

Type

conf

DOI

10.1109/CDC.1995.480264

Filename

480264