Title :
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
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;
Conference_Titel :
Decision and Control, 1995., Proceedings of the 34th IEEE Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-2685-7
DOI :
10.1109/CDC.1995.480264
