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

J. Schoukens, T. Dobrowiecki, R. Pintelon

Research output: Contribution to journalConference article

Abstract

This paper is the second of a series of two studying the asymptotic behaviour of non-parametric and parametric frequency domain identification methods to model linear dynamic systems in the presence of nonlinear distortions, using random multisine excitations. In Part I the non-parametric behavior of the transfer function measurement is studied. A related dynamic system (RLDS) is defined and linked to the classical results where the system is excited with normally distributed noise. In Part II the behavior of the parametric model is studied. Consistency is shown with respect to the RLDS system under some 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.

Original languageEnglish
Pages (from-to)1222-1227
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume2
Publication statusPublished - Dec 1 1995
EventProceedings of the 1995 34th IEEE Conference on Decision and Control. Part 1 (of 4) - New Orleans, LA, USA
Duration: Dec 13 1995Dec 15 1995

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ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization

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