| Summary: | Background. The procedure of identification of parameters of models of dynamic
objects by the method of regression analysis is considered. The substantiation and
choice of structure, types of components of the best discrete model, in the form of
difference equations of the order are given. The sequence of estimation of numerical
values of parameters of discrete model of object, correspondence of these parameters
to experimental data is discussed. We propose an integral quadratic criterion for
assessing the adequacy of the model using measurements at discrete times. The
basic approach of parametric identification is used-the least squares method, which,
while respecting linearity and discreteness, provides a simple and universal solution.
The questions of estimation of parameters of continuous models on the basis of values
of parameters of discrete model are considered
Results. The procedure of estimation of parameters of discrete and continuous
models of dynamic object on the basis of results of observation of input and output
variable on the set interval of time is developed.
Conclusions. The structure of the regression model must be consistent with the
structure of the continuous and discrete models based on the expected composition
of the poles and zeros. The number of zeros and zeros is determined from the condition
of the minimum standard deviation of the calculated values from the observed
values of the output variable. The optimal value of the poles and zeros is determined
by a complete search of possible options.
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