Algorithms of Sustainable Identification of Dynamic Objects in the Closed Control Line

Abstract

Algorithms for the stable identification of dynamic objects based on the results of their normal functioning in a closed control loop are presented. To improve the accuracy of the calculation of the parameters of the object, the regularization principle and pseudo-inversion methods based on the singular expansion are used. The resulted algorithms allow under certain noise signal conditions to carry out a stable identification of dynamic objects in a closed control loop.