collaborators

13 papers

eess.SY2026

Fast Risk Certification of Candidate Trajectories under Uncertain Time-Varying Constraints

Srimanta Santra, Oleksii Molodchyk, Matti Noack +1

This paper studies the certification of a fixed candidate trajectory on a finite certification grid under parametric uncertainty. For each constraint-time pair, we define a scalar…

eess.SY2026

Uncertainty Propagation under Residual Disturbances: A Smart-Home Case Study

Guanru Pan, Dirk Reinhardt, Sebastien Gros +1

This paper presents a data-driven framework for uncertainty propagation under unmeasured or statistically unmodeled (unstructured) disturbances. We consider residual disturbances,…

eess.SY2026

Towards Closed-loop Stability of Nonlinear Receding Horizon Games

Sophie Hall, Florian Dörfler, Timm Faulwasser

We analyze Receding Horizon Games without any MPC-like terminal ingredients. We show that recursive feasibility can be inferred from the turnpike phenomenon under mild assumptions.…

cs.LG2026

On Uniform Error Bounds for Kernel Regression under Non-Gaussian Noise

Johannes Teutsch, Oleksii Molodchyk, Marion Leibold +2

Providing non-conservative uncertainty quantification for function estimates derived from noisy observations remains a fundamental challenge in statistical machine learning, partic…

math.OC2026

Towards grid-aware multi-period flexibility aggregation - A constrained zonotope approach

Maurice Raetsch, Maísa Beraldo Bandeira, Christian Rehtanz +2

Aggregation schemes provide a means to reduce the computational complexity of power system operation by reducing the number of devices that are considered individually. This can be…

eess.SY2026

Data-Driven Power Flow for Radial Distribution Networks with Sparse Real-Time Data

Oleksii Molodchyk, Omid Mokhtari, Samuel Chevalier +2

Real-time control of distribution networks requires accurate information about the system state. In practice, however, such information is difficult to obtain because real-time mea…