تقرير
Structure and Optimization of Parameters for Neural Network Controllers in Automatic Control Systems
| العنوان: | Structure and Optimization of Parameters for Neural Network Controllers in Automatic Control Systems |
|---|---|
| المؤلفون: | Feofilov, Sergey, Khapkin, Dmitry, Kozyr, Andrey, Heiss, Eduard, Efromeev, Andrey |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Robotics, Electrical Engineering and Systems Science - Systems and Control, 68T05 (Primary) 93C10, 68T07 (Secondary), I.2.8, I.2.9 |
| الوصف: | The article outlines the methodology of structural and parametric synthesis of neural network controllers for controlling objects with limiters under incomplete information about the controlled object. Artificial neural networks are used to create controllers that are sequentially integrated into a control system with control objects. Reinforcement learning and pre-building a neural network imitator of the control object are used to synthesize the neural network controller. This approach is particularly effective when classical control system synthesis methods are not applicable due to significant nonlinearity and the difficulty in forming a mathematical model of the control object with the required accuracy. The proposed methods expand the class of technical systems for which direct synthesis of near-optimal control laws is possible. The robustness, adaptability and technical feasibility of neural network controllers make them interesting for practical applications. The main attention in the article is paid to the choice of neural network structure in the imitator and controller, formation of training samples taking into account the limitations of the control object. Comment: 7 pages with 11 figures |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2312.16510 |
| رقم الأكسشن: | edsarx.2312.16510 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |