collaborators

7 papers

math.OC2025

On Composite Foster Functions for a Class of Singularly Perturbed Stochastic Hybrid Inclusions

Jorge I. Poveda, Mahmoud Abdelgalil

We study sufficient conditions for stability and recurrence in a class of singularly perturbed stochastic hybrid dynamical systems. The systems considered combine multi-time-scale…

math.OC2025

On Event-Triggered Extremum Seeking via Standard and Lie-Bracket Averaging: A Hybrid Dynamical Systems Approach

Mahmoud Abdelgalil, Jorge I. Poveda

We introduce and analyze the stability of a class of event-triggered extremum-seeking algorithms designed to solve resource-aware, model-free, optimization problems. Leveraging rec…

math.OC2025

On the Instability of Nesterov's ODE under Non-Conservative Vector Fields

Daniel E. Ochoa, Mahmoud Abdelgalil, Jorge I. Poveda

We study the instability properties of Nesterov's ODE in non-conservative settings, where the driving term is not necessarily the gradient of a potential function. While convergenc…

math.OC2025

Control of Power Grids With Switching Equilibria: -Limit Sets and Input-to-State Stability

Mahmoud Abdelgalil, Vishal Shenoy, Guido Cavraro +2

This paper studies a power transmission system with both conventional generators (CGs) and distributed energy assets (DEAs) providing frequency control. We consider an operating co…

math.OC2025

On Persistently Resetting Learning Integrators: A Framework For Model-Free Feedback Optimization

Mahmoud Abdelgalil, Jorge I. Poveda

We study a novel class of algorithms for solving model-free feedback optimization problems in dynamical systems. The key novelty is the introduction of \emph{persistent resetting l…

math.OC2025

Prescribed-Time and Hyperexponential Concurrent Learning with Partially Corrupted Datasets: A Hybrid Dynamical Systems Approach

Daniel E. Ochoa, Jorge I. Poveda

We introduce a class of concurrent learning (CL) algorithms designed to solve parameter estimation problems with convergence rates ranging from hyperexponential to prescribed-time…