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

Farzaneh Karimi, Mohsen Mojiri, Roozbeh Izadi-Zamanabadi, Hossein Ramezani and Iman Izadi

International Journal of Systems Science, 2025, vol. 56, issue 8, 1834-1846

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.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2024.2434898 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:56:y:2025:i:8:p:1834-1846

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2024.2434898

Access Statistics for this article

International Journal of Systems Science is currently edited by Visakan Kadirkamanathan

More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().