2 citations · 4 across the 12 of their papers we have counts for
13 papers
Joint Chance Constrained Safe-Optimal Control
Niklas Schmid, Jared Miller, Tristan Zeller +3
We consider the finite-time optimal control of stochastic systems subject to a probabilistic constraint on the trajectories' safety. Such formulations are known as joint chance con…
Loss-aware distributionally robust optimization via trainable optimal transport ambiguity sets
Jonas Ohnemus, Marta Fochesato, Riccardo Zuliani +1
Optimal-Transport Distributionally Robust Optimization (OT-DRO) robustifies data-driven decision-making under uncertainty by capturing the sampling-induced statistical error via op…
Synthesis of safety certificates for discrete-time uncertain systems via convex optimization
Marta Fochesato, Han Wang, Antonis Papachristodoulou +1
We study the problem of co-designing control barrier functions and linear state feedback controllers for discrete-time linear systems affected by additive disturbances. For disturb…
Distributionally Robust LQG with Kullback-Leibler Ambiguity Sets
Marta Fochesato, Lucia Falconi, Mattia Zorzi +2
The Linear Quadratic Gaussian (LQG) controller is known to be inherently fragile to model misspecifications common in real-world situations. We consider discrete-time partially obs…
Distributionally Robust Optimization over Wasserstein Balls with i.i.d. Structure
Andrey Kharitenko, Marta Fochesato, Anastasios Tsiamis +2
We consider distributionally robust optimization problems where the uncertainty is modeled via a structured Wasserstein ambiguity set. Specifically, the ambiguity is restricted to…
Learn to Bid as a Price-Maker Wind Power Producer
Shobhit Singhal, Marta Fochesato, Liviu Aolaritei +1
Wind power producers (WPPs) participating in short-term power markets face significant imbalance costs due to their non-dispatchable and variable production. While some WPPs have a…
Joint Chance Constrained Optimal Control via Linear Programming
Niklas Schmid, Marta Fochesato, Tobias Sutter +1
We establish a linear programming formulation for the solution of joint chance constrained optimal control problems over finite time horizons. The joint chance constraint may repre…
Computing Optimal Joint Chance Constrained Control Policies
Niklas Schmid, Marta Fochesato, Sarah H. Q. Li +2
We consider the problem of optimally controlling stochastic, Markovian systems subject to joint chance constraints over a finite-time horizon. For such problems, standard Dynamic P…
Wasserstein Tube MPC with Exact Uncertainty Propagation
Liviu Aolaritei, Marta Fochesato, John Lygeros +1
We study model predictive control (MPC) problems for stochastic LTI systems, where the noise distribution is unknown, compactly supported, and only observable through a limited num…
Designing Optimal Personalized Incentive for Traffic Routing using BIG Hype algorithm
Panagiotis D. Grontas, Carlo Cenedese, Marta Fochesato +3
We study the problem of optimally routing plug-in electric and conventional fuel vehicles on a city level. In our model, commuters selfishly aim to minimize a local cost that combi…
Generalized uncertain Nash games: Reformulation and robust equilibrium seeking -- Extended version
Marta Fochesato, Filippo Fabiani, John Lygeros
We consider generalized Nash equilibrium problems (GNEPs) with linear coupling constraints affected by both local (i.e., agent-wise) and global (i.e., shared resources) disturbance…
BIG Hype: Best Intervention in Games via Distributed Hypergradient Descent
Panagiotis D. Grontas, Giuseppe Belgioioso, Carlo Cenedese +3
Hierarchical decision making problems, such as bilevel programs and Stackelberg games, are attracting increasing interest in both the engineering and machine learning communities.…
A Stackelberg game for incentive-based demand response in energy markets
Marta Fochesato, Carlo Cenedese, John Lygeros
In modern buildings renewable energy generators and storage devices are spreading, and consequently the role of the users in the power grid is shifting from passive to active. We d…