Robust Control Performance in Uncertain Environments: A Semi-Heuristic Gradient Descent Approach

Mohammed Elbadri Ahmed Hassan*, Ahmad Irham Jambak, Ismail Bayezit, Mehmet Turan Soylemez

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publicationProceedings of the 2023 International Conference on Instrumentation, Control, and Automation, ICA 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages149-154
Number of pages6
ISBN (Electronic)9798350301274
DOIs
Publication statusPublished - 2023
Event8th International Conference on Instrumentation, Control, and Automation, ICA 2023 - Jakarta, Indonesia
Duration: 9 Aug 202311 Aug 2023

Publication series

NameProceedings of the 2023 International Conference on Instrumentation, Control, and Automation, ICA 2023

Conference

Conference8th International Conference on Instrumentation, Control, and Automation, ICA 2023
Country/TerritoryIndonesia
CityJakarta
Period9/08/2311/08/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Gradient Descent
  • Interval Characteristic Polynomials
  • Kharitonov Theorem
  • Optimization

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