Multivariable Stochastic Newton-Based Extremum Seeking with Delays
Abstract
This paper presents a Newton-based stochastic extremum-seeking control method for real-time optimization in multi-input systems with distinct input delays. It combines predictor-based feedback and Hessian inverse estimation via stochastic perturbations to enable delay compensation with user-defined convergence rates. The method ensures exponential stability and convergence near the unknown extremum, even under long delays. It extends to multi-input, single-output systems with cross-coupled channels. Stability is analyzed using backstepping and infinite-dimensional averaging. Numerical simulations demonstrate its effectiveness in handling time-delayed channels, showcasing both the challenges and benefits of real-time optimization in distributed parameter settings.
Cite
@article{arxiv.2502.00861,
title = {Multivariable Stochastic Newton-Based Extremum Seeking with Delays},
author = {Paulo Cesar Souza Silva and Paulo Cesar Pellanda and Tiago Roux Oliveira},
journal= {arXiv preprint arXiv:2502.00861},
year = {2025}
}
Comments
28 pages, 13 figures