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Anti-windup higher derivative Newton-based extremum seeking under input saturation

Author

Listed:
  • Farzaneh Karimi
  • Mohsen Mojiri
  • Roozbeh Izadi-Zamanabadi
  • Hossein Ramezani
  • Iman Izadi

Abstract

The physical constraint of actuators in practical systems, such as actuator magnitude saturation, can significantly impact the behaviour of control systems. To address this issue, a fast learning mechanism is introduced in this paper for constrained input in higher derivatives Newton-based extremum seeking. The approach employs a constrained optimisation method with an anti-windup loop based on a wide range of penalty functions to adapt the search and prevent the violation of constraints, thereby avoiding windup of integral action in a controller. The practical asymptotic stability of the proposed algorithm is proven through a modified singular perturbation method, and its effectiveness is validated through simulations.

Suggested Citation

  • Farzaneh Karimi & Mohsen Mojiri & Roozbeh Izadi-Zamanabadi & Hossein Ramezani & Iman Izadi, 2025. "Anti-windup higher derivative Newton-based extremum seeking under input saturation," International Journal of Systems Science, Taylor & Francis Journals, vol. 56(8), pages 1834-1846, June.
    • Handle: RePEc:taf:tsysxx:v:56:y:2025:i:8:p:1834-1846
    DOI: 10.1080/00207721.2024.2434898
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