65

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.
 

  • Ссылка в интернете
  • DOI
  • Дата создание в систему UzSCI16-01-2023
  • Количество прочтений65
  • Дата публикации13-01-2023
  • Язык статьиIngliz
  • Страницы154-158
English

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.
 

Имя автора Должность Наименование организации
1 H I.S. lecturer Fergana branch of TUIT of the Department of "Information Technologies"
Название ссылки
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18 U.F. Mamirov. “Regular synthesis of adaptive control systems for uncertain dynamic objects”, 2021. 215
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