output
20062024
most citedScience vs Conspiracy: collective narratives in the age of (mis)information

662 citations

Showing math.OCShow all

6 papers · 1 filter

math.OC20237 cited

Specification-Guided Critical Scenario Identification for Automated Driving

Adam Molin, Edgar A. Aguilar, Dejan Ničković +3

To test automated driving systems, we present a case study for finding critical scenarios in driving environments guided by formal specifications. To that aim, we devise a framewor…

math.OC2019140 cited

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…

math.OC20197 cited

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…

math.OC20161 cited

Stochastic economic model predictive control for Markovian switching systems

Pantelis Sopasakis, Domagoj Herceg, Panagiotis Patrinos +1

The optimization of process economics within the model predictive control (MPC) formulation has given rise to a new control paradigm known as economic MPC (EMPC). Several authors h…

math.OC20143 cited

Fixed-Point Constrained Model Predictive Control of Spacecraft Attitude

Alberto Guiggiani, Ilya Kolmanovsky, Panagiotis Patrinos +1

The paper develops a Model Predictive Controller for constrained control of spacecraft attitude with reaction wheel actuators. The controller exploits a special formulation of the…

math.OC201412 cited

Douglas-Rachford Splitting: Complexity Estimates and Accelerated Variants

Panagiotis Patrinos, Lorenzo Stella, Alberto Bemporad

We propose a new approach for analyzing convergence of the Douglas-Rachford splitting method for solving convex composite optimization problems. The approach is based on a continuo…