
Digital Library of the
European Council for Modelling and Simulation 
Title: 
Distributed Parameter Model Oriented Identification 
Authors: 
Mircea CehanRacovita 
Published in: 
(2006).ECMS
2006 Proceedings edited by: W. Borutzky, A. Orsoni, R. Zobel. European
Council for Modeling and Simulation. doi:10.7148/2006 ISBN:
0955301807 20^{th}
European Conference on Modelling and Simulation, Bonn,
May 2831, 2006 
Citation
format: 
CehanRacovita, M. (2006). Distributed Parameter
Model Oriented Identification. ECMS 2006 Proceedings edited by: W. Borutzky, A. Orsoni, R. Zobel (pp. 445449). European
Council for Modeling and Simulation. doi:10.7148/20060445 
DOI: 
http://dx.doi.org/10.7148/20060445 
Abstract: 
By means of
mathematically defined digital filters, the disturbance affecting the system
response may be eliminated and the real response recovered. Thereby a multivariable exponential test signal is assumed, but any other
type of input is also pertinent. This achievement involves both a functional
and a stochastic component. The former consists in the proved property that a
multivariable function given over a finite interval may be approximately
expressed by a product of functions of only one variable. Further, each such
factor is expandable in a finite sum of exponential terms. The latter
component consists in the low probability of coincidence regarding the test
signal exponent and any exponent of the disturbance (approximate) spectrum. The developed procedure
enables to estimate the constant coefficients included in a distributed
parameter model of the process. Short
observation time, test signal / noise small ration, the good accuracy of the
model estimation and simple identification algorithm will be achieved. These
features are due to the method peculiarity, to operate with any incipient
segment of the response, and to the simple structure and good selectivity of
the proposed digital filters. One may give up the test signal use, by having recoursed to exponential decomposition of the actual system
input 
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