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.
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.
| № | Muallifning F.I.Sh. | Lavozimi | Tashkilot nomi |
|---|---|---|---|
| 1 | H I.S. | lecturer | Fergana branch of TUIT of the Department of "Information Technologies" |
| № | Havola nomi |
|---|---|
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