Digital Library

of the European Council for Modelling and Simulation



Distributed Parameter Model Oriented Identification


Mircea Cehan-Racovita

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: 0-9553018-0-7


20th European Conference on Modelling and Simulation,

Bonn, May 28-31, 2006


Citation format:

Cehan-Racovita, M. (2006). Distributed Parameter Model Oriented Identification. ECMS 2006 Proceedings edited by: W. Borutzky, A. Orsoni, R. Zobel (pp. 445-449). European Council for Modeling and Simulation. doi:10.7148/2006-0445



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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