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Robust transfer function identification via an enhanced magnitude vector fitting algorithm

L De Tommasi, B Gustavsen and Tom Dhaene UGent (2010) IET CONTROL THEORY AND APPLICATIONS. 4(7). p.1169-1178
abstract
The study introduces an enhanced version of the magnitude vector fitting (magVF) algorithm, a robust procedure for the identification of a transfer function from magnitude frequency domain data. The approach is based on the rational approximation of the magnitude square function with enforcement of symmetric poles and zeros, followed by the elimination of poles and zeros located in the right half-plane. The obtained transfer function is stable and of minimum-phase shift type. Robustness and accuracy of the basic magVF algorithm are enhanced by enforcing that the magnitude square rational function is non-negative definite and by introducing a new method to remove purely imaginary conjugate poles from the approximation. Practical application of the proposed approach is demonstrated for measured transformer responses and transmission line propagation functions.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
FREQUENCY-DOMAIN RESPONSES, RATIONAL APPROXIMATION, TRANSMISSION-LINES, TRANSIENTS
journal title
IET CONTROL THEORY AND APPLICATIONS
IET Contr. Theory Appl.
volume
4
issue
7
pages
1169 - 1178
Web of Science type
Article
Web of Science id
000279544400006
JCR category
ENGINEERING, ELECTRICAL & ELECTRONIC
JCR impact factor
1.283 (2010)
JCR rank
94/247 (2010)
JCR quartile
2 (2010)
ISSN
1751-8644
DOI
10.1049/iet-cta.2009.0025
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1140704
handle
http://hdl.handle.net/1854/LU-1140704
date created
2011-02-07 11:12:10
date last changed
2016-12-19 15:45:26
@article{1140704,
  abstract     = {The study introduces an enhanced version of the magnitude vector fitting (magVF) algorithm, a robust procedure for the identification of a transfer function from magnitude frequency domain data. The approach is based on the rational approximation of the magnitude square function with enforcement of symmetric poles and zeros, followed by the elimination of poles and zeros located in the right half-plane. The obtained transfer function is stable and of minimum-phase shift type. Robustness and accuracy of the basic magVF algorithm are enhanced by enforcing that the magnitude square rational function is non-negative definite and by introducing a new method to remove purely imaginary conjugate poles from the approximation. Practical application of the proposed approach is demonstrated for measured transformer responses and transmission line propagation functions.},
  author       = {De Tommasi, L and Gustavsen, B and Dhaene, Tom},
  issn         = {1751-8644},
  journal      = {IET CONTROL THEORY AND APPLICATIONS},
  keyword      = {FREQUENCY-DOMAIN RESPONSES,RATIONAL APPROXIMATION,TRANSMISSION-LINES,TRANSIENTS},
  language     = {eng},
  number       = {7},
  pages        = {1169--1178},
  title        = {Robust transfer function identification via an enhanced magnitude vector fitting algorithm},
  url          = {http://dx.doi.org/10.1049/iet-cta.2009.0025},
  volume       = {4},
  year         = {2010},
}

Chicago
De Tommasi, L, B Gustavsen, and Tom Dhaene. 2010. “Robust Transfer Function Identification via an Enhanced Magnitude Vector Fitting Algorithm.” Iet Control Theory and Applications 4 (7): 1169–1178.
APA
De Tommasi, L, Gustavsen, B., & Dhaene, T. (2010). Robust transfer function identification via an enhanced magnitude vector fitting algorithm. IET CONTROL THEORY AND APPLICATIONS, 4(7), 1169–1178.
Vancouver
1.
De Tommasi L, Gustavsen B, Dhaene T. Robust transfer function identification via an enhanced magnitude vector fitting algorithm. IET CONTROL THEORY AND APPLICATIONS. 2010;4(7):1169–78.
MLA
De Tommasi, L, B Gustavsen, and Tom Dhaene. “Robust Transfer Function Identification via an Enhanced Magnitude Vector Fitting Algorithm.” IET CONTROL THEORY AND APPLICATIONS 4.7 (2010): 1169–1178. Print.