Generalized Multi-Constraint Extremum Seeking
Optimization and Control
2025-10-09 v1
Abstract
We generalize the Safe Extremum Seeking algorithm to address the minimization of an unknown objective function subject to multiple unknown inequality and equality constraints, relying on recent results of gradient flow systems. These constraints may represent safety or other critical conditions. The proposed ES algorithm functions as a general nonlinear programming tool, offering practical maintenance of all constraints and semiglobal practical asymptotic stability, utilizing a Lyapunov argument on the penalty function and the set-valued Lie derivative. The efficacy of the algorithm is demonstrated on a 2D problem.
Cite
@article{arxiv.2510.06403,
title = {Generalized Multi-Constraint Extremum Seeking},
author = {Alan Williams and Jorge Cortés and Alexander Scheinker},
journal= {arXiv preprint arXiv:2510.06403},
year = {2025}
}