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REGULAR ALGORITHM FOR PARAMETRIC IDENTIFICATION OF A LINEAR DYNAMIC OBJECT WITH RANDOM PARAMETERS

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The questions of constructing regular algorithms for parametric identification of a linear dynamic plant with random parameters with guaranteed mean square accuracy are considered. To estimate the vector of unknown parameters of a dynamic system, a sequential version of the least squares estimates is used. When solving the considered ill-posed problem, a regular algorithm is used. When choosing the regularization parameter, the methods of quasi-optimality and cross-significance were used in the work. The considered algorithms make it possible to produce a stable identification of a linear dynamic system with random parameters, and thereby improve the accuracy of the synthesized adaptive control system for the considered class of objects.

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# linear dynamic object with rando# parametric identification

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Foydalanilgan adabiyotlar

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