Abstract
Designing a robust controller for systems with parameter uncertainties is a complex and demanding task. Traditional deterministic and probabilistic approaches may fall short in providing efficient and satisfactory solutions. To address this challenge, we propose a semi-heuristic approach that exploits the Kharitonov theorem to establish an initial point for the gradient descent algorithm. Through an iterative optimization process that incorporates user-defined performance criteria, our approach provide a robust controller with respect to presence of system uncertainties. Numerical simulations validate the effectiveness of our proposed method and highlight its superiority in addressing robust control problems compared with auto-tuned ΡΠ) controller.
Original language | English |
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Title of host publication | Proceedings of the 2023 International Conference on Instrumentation, Control, and Automation, ICA 2023 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 149-154 |
Number of pages | 6 |
ISBN (Electronic) | 9798350301274 |
DOIs | |
Publication status | Published - 2023 |
Event | 8th International Conference on Instrumentation, Control, and Automation, ICA 2023 - Jakarta, Indonesia Duration: 9 Aug 2023 → 11 Aug 2023 |
Publication series
Name | Proceedings of the 2023 International Conference on Instrumentation, Control, and Automation, ICA 2023 |
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Conference
Conference | 8th International Conference on Instrumentation, Control, and Automation, ICA 2023 |
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Country/Territory | Indonesia |
City | Jakarta |
Period | 9/08/23 → 11/08/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- Gradient Descent
- Interval Characteristic Polynomials
- Kharitonov Theorem
- Optimization