7 citations · 18 across the 17 of their papers we have counts for
4 papers · 1 filter
Pick-to-Learn Calibration of an MPC Policy for an Origin-to-Destination Flight Problem
Marco C. Campi, Simone Garatti
This paper illustrates the Pick-to-Learn methodology applied to the calibration of a Model Predictive Control policy. While developed around a specific example, the presentation is…
Pick-to-Learn for Systems and Control: Data-driven Synthesis with State-of-the-art Safety Guarantees
Dario Paccagnan, Daniel Marks, Marco C. Campi +1
Data-driven methods have become paramount in modern systems and control problems characterized by growing levels of complexity. In safety-critical environments, deploying these met…
An incremental scenario approach for building energy management with uncertain occupancy
Arman Karshenas, Kostas Margellos, Simone Garatti
We deal with the problem of energy management in buildings subject to uncertain occupancy. To this end, we formulate this as a finite horizon optimization program and optimize with…
Performance assessment and design of abstracted models for stochastic hybrid systems through a randomized approach
M. Prandini, S. Garatti, R. Vignali
In this paper, a simulation-based method for the analysis and design of abstracted models for a stochastic hybrid system is proposed. The accuracy of a model is evaluated in terms…