activity
20242026
collaborators

5 papers

math.DS2026

A Closed-loop Framework to Discriminate Models Using Optimal Control

Laurent Pagnier, Melvyn Tyloo, Akshita Jindal +2

Predicting the response of an observed system to a known input is a fruitful first step to accurately control the system's dynamics. Despite the recent advances in fully data-drive…

eess.SY2026

Accurate Data-Based State Estimation from Power Loads Inference in Electric Power Grids

Philippe Jacquod, Laurent Pagnier, Daniel J. Gauthier

Accurate state estimation is a crucial requirement for the reliable operation and control of electric power systems. Here, we construct a data-driven, numerical method to infer mis…

math.OC2026

Real-Time Dynamic N-1 Screening: Identifying High-Risk Lines and Transformers After Common Faults

Ayrton Almada, Laurent Pagnier, Igal Goldshtein +3

Power system operators routinely perform N-1 contingency analysis, yet conventional tools provide limited guidance on which lines or transformers deserve heightened attention durin…

math.DS2025

Real-Time Stochastic Assessment of Dynamic N-1 Grid Contingencies

Ayrton Almada, Laurent Pagnier, Igal Goldshtein +3

Power system operators need tools for rapid, real-time counterfactual assessments of grid security under fast-changing conditions. Traditional N-1 contingency analysis lacks dynami…

eess.SY2024

Physics-Guided Actor-Critic Reinforcement Learning for Swimming in Turbulence

Christopher Koh, Laurent Pagnier, Michael Chertkov

Turbulent diffusion causes particles placed in proximity to separate. We investigate the required swimming efforts to maintain an active particle close to its passively advected co…