140 citations · 141 across the 5 of their papers we have counts for
6 papers
On the design of regularized explicit predictive controllers from input-output data
Valentina Breschi, Andrea Sassella, Simone Formentin
On the wave of recent advances in data-driven predictive control, we present an explicit predictive controller that can be constructed from a batch of input/output data only. The p…
Learning explicit predictive controllers: theory and applications
Andrea Sassella, Valentina Breschi, Simone Formentin
In this paper, we deal with data-driven predictive control of linear time-invariant (LTI) systems. Specifically, we show for the first time how explicit predictive laws can be lear…
Direct data-driven model-reference control with Lyapunov stability guarantees
Valentina Breschi, Claudio De Persis, Simone Formentin +1
In this work, we introduce a novel data-driven model-reference control design approach for unknown linear systems with fully measurable state. The proposed control action is compos…
Learning-based hierarchical control of water reservoir systems
Pauline Kergus, Simone Formentin, Matteo Giuliani +1
The optimal control of a water reservoir systems represents a challenging problem, due to uncertain hydrologic inputs and the need to adapt to changing environment and varying cont…
Experimental Automatic Calibration of a Semi-Active Suspension Controller via Bayesian Optimization
Gianluca Savaia, Youngil Sohn, Simone Formentin +3
The End-of-Line (EoL) calibration of semi-active suspension systems for road vehicles is usually a critical and expensive task, needing a team of vehicle and control experts as wel…
Performance-oriented model learning for data-driven MPC design
Dario Piga, Marco Forgione, Simone Formentin +1
Model Predictive Control (MPC) is an enabling technology in applications requiring controlling physical processes in an optimized way under constraints on inputs and outputs. Howev…