Bounds on modeling error due to weak nonlinear distortions

Author

Dobrowiecki, Tadeusz P. ; Schoukens, Johan

Author_Institution

Dept. of Meas. & Inf. Syst., Budapest Univ. of Technol. & Econ., Hungary

Volume

1

fYear

2001

fDate

21-23 May 2001

Firstpage

14

Abstract

Small nonlinearities affect the measurement of the frequency response function (FRF). The measured best linear approximation to the (nonlinear) system becomes offset from G₀(jω) (the underlying linear system) and the measurements appear noisy due to the presence of the stochastic nonlinear component. Using repeated measurements the characteristics can be smoothed; the bias however presents a problem. In this contribution the authors show, that for a particular class of nonlinear systems, the unknown bias can be bounded even if no a priori information is available about the order or the magnitude of the nonlinear component

Keywords

Volterra equations; frequency response; identification; linear systems; measurement errors; modelling; nonlinear systems; Volterra system; Wiener-Hammerstein property; frequency response function; linear approximation; modeling error bounds; relative variance; repeated measurements; small nonlinearities; stochastic nonlinear component; underlying linear system; unknown bias; weak nonlinear distortions; Distortion measurement; Linear systems; Noise level; Noise measurement; Nonlinear distortion; Nonlinear dynamical systems; Pollution measurement; Power measurement; Stochastic systems; Uniform resource locators;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 2001. IMTC 2001. Proceedings of the 18th IEEE

Conference_Location

Budapest

ISSN

1091-5281

Print_ISBN

0-7803-6646-8

Type

conf

DOI

10.1109/IMTC.2001.928780

Filename

928780