Generating robust starting values for frequency-domain transfer function estimation

Automatica ◽  
1999 ◽  
Vol 35 (5) ◽  
pp. 965-972 ◽  
Author(s):  
Yves Rolain ◽  
Rik Pintelon
Keyword(s):  
Transfer Function ◽  
Frequency Domain ◽  
Function Estimation ◽  
Starting Values ◽  
Domain Transfer

scholarly journals Convergence Analysis of EFOP Estimate Based on Frequency Domain Smoothing

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Yulai Zhang ◽  
Kueiming Lo ◽  
Yang Su
Keyword(s):  
Transfer Function ◽  
Frequency Domain ◽  
Optimal Parameter ◽  
Integral Form ◽  
Noise Signal ◽  
Function Estimation ◽  
Frequency Domain Methods ◽  
Frequency Window ◽  
The Time Domain ◽  
Domain Transfer

The classic methods for frequency domain transfer function estimation such as the Empirical Transfer Function Estimate (ETFE) and cross spectral method do not work well when the noise signal is complex. Combines the time domain and frequency domain methods the Empirical Frequency-domain Optimal Parameter (EFOP) Estimate was presented. It could improve the precision of system's transfer function estimation and identification efficiency. The convergence of the EFOP based on frequency domain smoothing is investigated in this paper. The transfer function is weighted by a frequency window and the GPE criterion is extended to the integral form. Convergence rate and consistent properties for the EFOP estimate are given. Finally, some simulation results are included to illustrate the advantage of the EFOP based smoothing method.

Structural Parameter Identification in the Frequency Domain: The Use of Overdetermined Systems

1987 ◽  
Vol 109 (2) ◽  
pp. 120-123 ◽  
Author(s):  
S. G. Braun ◽  
Y. M. Ram
Keyword(s):  
Transfer Function ◽  
Parameter Identification ◽  
Frequency Domain ◽  
Rational Function ◽  
Least Square ◽  
Structural Parameter ◽  
Overdetermined Systems ◽  
The Matrix ◽  
Domain Transfer

This paper deals with the fitting of a rational function to an experimentally determined frequency domain transfer function. Examples show that the use of overdetermined fitted systems improve the identification in noisy situations. A method is presented, enabling the determination of the number of zero/poles of the system, and the relation to the rank of the matrix used in a least square identification method.

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