1.2k citations · 1.7k across the 52 of their papers we have counts for
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Efficient Calibration of Embedded MPC
Marco Forgione, Dario Piga, Alberto Bemporad
Model Predictive Control (MPC) is a powerful and flexible design tool of high-performance controllers for physical systems in the presence of input and output constraints. A challe…
Active preference learning based on radial basis functions
Alberto Bemporad, Dario Piga
This paper proposes a method for solving optimization problems in which the decision-maker cannot evaluate the objective function, but rather can only express a preference such as…
An efficient bounded-variable nonlinear least-squares algorithm for embedded MPC
Nilay Saraf, Alberto Bemporad
This paper presents a new approach to solve linear and nonlinear model predictive control (MPC) problems that requires small memory footprint and throughput and is particularly sui…
Global optimization via inverse distance weighting and radial basis functions
Alberto Bemporad
Global optimization problems whose objective function is expensive to evaluate can be solved effectively by recursively fitting a surrogate function to function samples and minimiz…
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…
Uncertainty-aware demand management of water distribution networks in deregulated energy markets
Pantelis Sopasakis, Ajay K. Sampathirao, Alberto Bemporad +1
We present an open-source solution for the operational control of drinking water distribution networks which accounts for the inherent uncertainty in water demand and electricity p…
Practical Reinforcement Learning of Stabilizing Economic MPC
Mario Zanon, Sébastien Gros, Alberto Bemporad
Reinforcement Learning (RL) has demonstrated a huge potential in learning optimal policies without any prior knowledge of the process to be controlled. Model Predictive Control (MP…