8 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…
Scenario-Based Stochastic MPC for Energy Hubs with EV Fleets Under Persistent Grid Outages
Kobena Badu Enyam, Cara Koepele, Timothy Asare +2
Emissions reduction and resilience to outages motivate the adoption of renewable microgrids. Surprisingly, research integrating both probabilistic grid outages and electric vehicle…
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…
Differentiable-by-design Nonlinear Optimization for Model Predictive Control
Riccardo Zuliani, Efe C. Balta, John Lygeros
Nonlinear optimization-based control policies, such as those those arising in nonlinear Model Predictive Control, have seen remarkable success in recent years. These policies requi…
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…
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…