Abstract
Algorithms for adaptive identification of parameters of stochastic control objects are given. The task of identifying a managed object is reduced to the task of estimating the parameters of the regression model on the basis of the generalized least-squares method. Algorithms for the sustainable estimation of object parameters on the basis of stable recurrent procedures are presented. These algorithms allow us to effectively calculate the desired parameters of an identified object under the conditions of the time correlation of the noise acting on the object.
First Page
74
Last Page
77
References
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Recommended Citation
Yusupov, Y.А
(2018)
"Algorithms for adaptive identification of parameters of stochastic control objects,"
Chemical Technology, Control and Management: Vol. 2018:
Iss.
2, Article 14.
DOI: https://doi.org/10.34920/2018.3.74-77
