140 citations · 196 across the 14 of their papers we have counts for
6 papers · 1 filter
Uncertainty-aware data-driven predictive control in a stochastic setting
Valentina Breschi, Marco Fabris, Simone Formentin +1
Data-Driven Predictive Control (DDPC) has been recently proposed as an effective alternative to traditional Model Predictive Control (MPC), in that the same constrained optimizatio…
Hourly operation of a regulated lake via Model Predictive Control
Raffaele G. Cestari, Andrea Castelletti, Simone Formentin
The optimal operation of regulated lakes is a challenging task involving conflicting objectives, ranging from controlling lake levels to avoid floods and low levels to water supply…
The Twin-in-the-Loop approach for vehicle dynamics control
Federico Dettù, Simone Formentin, Sergio Matteo Savaresi
In vehicle dynamics control, engineering a suitable regulator is a long and costly process. The starting point is usually the design of a nominal controller based on a simple contr…
Data-driven design of explicit predictive controllers using model-based priors
Valentina Breschi, Andrea Sassella, Simone Formentin
In this paper, we propose a data-driven approach to derive explicit predictive control laws, without requiring any intermediate identification step. The keystone of the presented s…
Twin-in-the-loop state estimation for vehicle dynamics control: theory and experiments
Giorgio Riva, Simone Formentin, Matteo Corno +1
In vehicle dynamics control, many variables of interest cannot be directly measured, as sensors might be costly, fragile, or even not available. Therefore, real-time estimation tec…
Data-driven predictive control in a stochastic setting: a unified framework
Valentina Breschi, Alessandro Chiuso, Simone Formentin
Data-driven predictive control (DDPC) has been recently proposed as an effective alternative to traditional model-predictive control (MPC) for its unique features of being time-eff…