74686

Автор(ы): 

Автор(ов): 

2

Параметры публикации

Тип публикации: 

Доклад

Название: 

Parameter Estimation-Based Observer for Linear Systems with Polynomial Overparameterization

Электронная публикация: 

Да

ISBN/ISSN: 

979-8-3503-1543-1

DOI: 

10.1109/MED59994.2023.10185889

Наименование конференции: 

  • 31st Mediterranean Conference on Control and Automation (MED 2023, Limassol, Cyprus)

Наименование источника: 

  • Proceedings of 31st Mediterranean Conference on Control and Automation (MED 2023)

Город: 

  • Limassol

Издательство: 

  • IEEE

Год издания: 

2023

Страницы: 

795-799 https://ieeexplore.ieee.org/document/10185889
Аннотация
An adaptive state observer is proposed for a class of overparametrized uncertain linear time-invariant systems without restrictive requirement of their representation in the observer canonical form. It evolves the method of Generalized Parameters Estimation-Based Observer design and, therefore, (i) does not require to identify Luenberger correction gain parameters, (ii) forms states using algebraic rather than differential equation. Additionally, the developed observer is applicable to systems with unknown output matrix and ensures exponential convergence of unmeasured state observation error under weak requirement of the regressor finite excitation. The effectiveness of the proposed solution is supported by simulation results.

Библиографическая ссылка: 

Глущенко А.И., Ласточкин К.А. Parameter Estimation-Based Observer for Linear Systems with Polynomial Overparameterization / Proceedings of 31st Mediterranean Conference on Control and Automation (MED 2023). Limassol: IEEE, 2023. С. 795-799 https://ieeexplore.ieee.org/document/10185889.