74860

Автор(ы): 

Автор(ов): 

3

Параметры публикации

Тип публикации: 

Статья в журнале/сборнике

Название: 

Robust Tracking as Constrained Optimization by Uncertain Dynamic Plant: Mirror Descent Method and ASG—Version of Integral Sliding Mode Control

ISBN/ISSN: 

ISSN 2078-2489

DOI: 

10.3390/math11194112

Наименование источника: 

  • Mathematics

Обозначение и номер тома: 

Vol.11, Iss. 19

Город: 

  • Basel, Switzerland

Издательство: 

  • MDPI

Год издания: 

2023

Страницы: 

4112 (1-15)
Аннотация
A class of controlled objects is considered, the dynamics of which are determined by a vector system of ordinary differential equations with a partially known right-hand side. It is presumed that the state variables and their velocities can be measured. Designing a robust tracking controller under some constraints to admissible state variables is the research goal. This construction, which extends the results for the average subgradient technique (ASG), and is an update of the subgradient descent technique (SDM) and integral sliding mode (ISM) approach, is realized by using the Legendre–Fenchel transform. A two-link robot manipulator with three revolute joints, powered by individual PMDC motors, is presented as an illustrative example of the suggested approach implementation.

Библиографическая ссылка: 

Назин А.В., Алазки Х.H., Позняк А.С. Robust Tracking as Constrained Optimization by Uncertain Dynamic Plant: Mirror Descent Method and ASG—Version of Integral Sliding Mode Control // Mathematics. 2023. Vol.11, Iss. 19. С. 4112 (1-15).