48 citations · 294 across the 36 of their papers we have counts for
4 papers · 1 filter
Parametrizations of All Stable Closed-loop Responses: From Theory to Neural Network Control Design
Clara Lucía Galimberti, Luca Furieri, Giancarlo Ferrari-Trecate
The complexity of modern control systems necessitates architectures that achieve high performance while ensuring robust stability, particularly for nonlinear systems. In this work,…
Learning to Boost the Performance of Stable Nonlinear Systems
Luca Furieri, Clara Lucía Galimberti, Giancarlo Ferrari-Trecate
The growing scale and complexity of safety-critical control systems underscore the need to evolve current control architectures aiming for the unparalleled performances achievable…
Optimal distributed control with stability guarantees by training a network of neural closed-loop maps
Danilo Saccani, Leonardo Massai, Luca Furieri +1
This paper proposes a novel approach to improve the performance of distributed nonlinear control systems while preserving stability by leveraging Deep Neural Networks (DNNs). We bu…
Learning to optimize with convergence guarantees using nonlinear system theory
Andrea Martin, Luca Furieri
The increasing reliance on numerical methods for controlling dynamical systems and training machine learning models underscores the need to devise algorithms that dependably and ef…