Apply Cross Spectral Analysis to Transfer Function Model Identification

DOI

10.2991/meic-14.2014.232How to use a DOI?

Keywords

cross spectrum; transfer function models; frequency response function; cross spectral analysis; Fourier transform

Abstract

Transfer function models is of considerable interest in economics, engineering, biology, and many other fields. Models of this kind can describe not only the behavior of industrial processes but also that of economic and business systems. Transfer function model building is important because it is only when the dynamic characteristics of a system are understood that intelligent direction, manipulation, and control of the system is possible. Engineering methods for estimating transfer functions are usually based on the choice of special inputs to the system such as step and sine wave inputs and “pulse” inputs. These methods have been useful when the system is affected by small amounts of noise but are less satisfactory otherwise. In the presence of appreciable noise, it is necessary to use statistical methods for estimating the transfer function. In this paper we show that an alternative method for identifying transfer function models, which does not require prewhitening of the input, can be based on spectral analysis. Furthermore, it is easily generalized to multiple inputs.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Changjiang Zheng
AU  - Qifang Chen
AU  - Linbai Tong
AU  - Youxiang Cui
PY  - 2014/11
DA  - 2014/11
TI  - Apply Cross Spectral Analysis to Transfer Function Model Identification
BT  - Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 1041
EP  - 1044
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-14.2014.232
DO  - 10.2991/meic-14.2014.232
ID  - Zheng2014/11
ER  -