Bounded Extremum Seeking for Single-Variable Static Map using State Transformation - INRIA - Institut National de Recherche en Informatique et en Automatique
Conference Papers Year : 2024

Bounded Extremum Seeking for Single-Variable Static Map using State Transformation

Abstract

We solve a gradient based bounded extremum seeking problem for single-variable static maps in the presence of time-varying piecewise continuous measurement uncertainty. Instead of using previously reported averaging-based methods, we introduce a new state transformation, allowing us to use new comparison function and generalized Lyapunov function approaches to obtain our ultimate bounds on the parameter estimation error. We illustrate significant advantages of our new method, including less restrictive conditions on the extremum seeking parameters, as compared with previous methods.
Fichier principal
Vignette du fichier
CDC24ExtremumSeeking.pdf (267.16 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04704546 , version 1 (21-09-2024)

Licence

Identifiers

  • HAL Id : hal-04704546 , version 1

Cite

Frederic Mazenc, Michael Malisoff, Emilia Fridman. Bounded Extremum Seeking for Single-Variable Static Map using State Transformation. CDC 2024 - 63rd IEEE Conference on Decision and Control, Dec 2024, Milan, Italy. ⟨hal-04704546⟩
136 View
30 Download

Share

More