<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The paper presents a novel approach to approximation of a linear transfer function model, based on dynamic properties represented by a frequency response, e.g., determined as a result of discrete-time identification. The approximation is derived for minimization of a non-quadratic performance index. This index can be determined as an exponent or absolute norm of an error. Two algorithms for determination of the approximation coefficients are considered, a batch processing one and a recursive scheme, based on the well-known on-line identification algorithm. The proposed approach is not sensitive to local outliers present in the original frequency response. Application of the approach and its features are presented on examples of two simple dynamic systems.</p></abstract>

The paper presents a novel approach to approximation of a linear transfer function model, based on dynamic properties represented by a frequency response, e.g., determined as a result of discrete-time identification. The approximation is derived for minimization of a non-quadratic performance index. This index can be determined as an exponent or absolute norm of an error. Two algorithms for determination of the approximation coefficients are considered, a batch processing one and a recursive scheme, based on the well-known on-line identification algorithm. The proposed approach is not sensitive to local outliers present in the original frequency response. Application of the approach and its features are presented on examples of two simple dynamic systems.

Approximation of a linear dynamic process model using the frequency approach and a non-quadratic measure of the model error

Institute of Automatic Control and Robotics Warsaw University of Technology, ul. A. Boboli 8, 02-525 Warsaw, Poland

International Journal of Applied Mathematics and Computer Science

The paper presents a novel approach to approximation of a linear transfer function model, based on dynamic properties represented by a frequency response,...

Approximation of a linear dynamic process model using the frequency approach and a non-quadratic measure of the model error

Published Online: Mar 25, 2014

Page range: 99 - 109

DOI: https://doi.org/10.2478/amcs-2014-0008

Keywords
approximation method, frequency domain, non-quadratic criterion, recursive algorithm.

This content is open access.

Approximation of a linear dynamic process model using the frequency approach and a non-quadratic measure of the model error

Published Online: Mar 25, 2014

Page range: 99 - 109

DOI: https://doi.org/10.2478/amcs-2014-0008

Keywordsapproximation method, frequency domain, non-quadratic criterion, recursive algorithm.

This content is open access.

Keywords
approximation method, frequency domain, non-quadratic criterion, recursive algorithm.