1 citations · 1 across the 3 of their papers we have counts for
Showing eess.SYShow all
2 papers · 1 filter
eess.SY2026
A subspace approach to data-driven predictive control for linear parameter-varying systems
Federico Porcari, Chris Verhoek, Valentina Breschi +2
This paper presents a subspace data-driven predictive control method for linear parameter-varying (LPV) systems. Starting from an affine LPV state-space model in innovation form, w…
eess.SY2025
eXplainable AI for data driven control: an inverse optimal control approach
Federico Porcari, Donatello Materassi, Simone Formentin
Understanding the behavior of black-box data-driven controllers is a key challenge in modern control design. In this work, we propose an eXplainable AI (XAI) methodology based on I…