1 citations · 2 across the 7 of their papers we have counts for
7 papers
Meta-learning of data-driven controllers with automatic model reference tuning: theory and experimental case study
Riccardo Busetto, Valentina Breschi, Federica Baracchi +1
Data-driven control offers a viable option for control scenarios where constructing a system model is expensive or time-consuming. Nonetheless, many of these algorithms are not ent…
SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study
Aurelio Raffa Ugolini, Valentina Breschi, Andrea Manzoni +1
In this work we analyze the effectiveness of the Sparse Identification of Nonlinear Dynamics (SINDy) technique on three benchmark datasets for nonlinear identification, to provide…
Explainable data-driven modeling via mixture of experts: towards effective blending of grey and black-box models
Jessica Leoni, Valentina Breschi, Simone Formentin +1
Traditional models grounded in first principles often struggle with accuracy as the system's complexity increases. Conversely, machine learning approaches, while powerful, face cha…
Meta-learning for model-reference data-driven control
Riccardo Busetto, Valentina Breschi, Simone Formentin
One-shot direct model-reference control design techniques, like the Virtual Reference Feedback Tuning (VRFT) approach, offer time-saving solutions for the calibration of fixed-stru…
Model predictive control with dynamic move blocking
Valentina Breschi, Simone Formentin, Alberto Leva
Model Predictive Control (MPC) has proven to be a powerful tool for the control of systems with constraints. Nonetheless, in many applications, a major challenge arises, that is fi…
META-SMGO-: similarity as a prior in black-box optimization
Riccardo Busetto, Valentina Breschi, Simone Formentin
When solving global optimization problems in practice, one often ends up repeatedly solving problems that are similar to each others. By providing a rigorous definition of similari…