collaborators

6 papers

math.PR2026

Extreme points of sets of probability measures and -divergences

Gerrit Bauch, Max Nendel, Alessandro Sgarabottolo

In this work, we prove several equivalent characterizations of the extreme points of convex sets of probability measures of the form , where $\mathc…

eess.SY2026

Least Costly Space-Filling Experiment Design for the Identification of a Nonlinear System

Máté Kiss, Maarten Schoukens, Roland Tóth

The quality of an estimated nonlinear model highly depends on the data quality that was used for the system identification. By using a Gaussian Process-based optimal input design a…

cs.RO2026

Robust Adaptive Predictive Control for Hook-Based Aerial Transportation Between Moving Platforms

Péter Antal, Andrea Carron, Melanie Zeilinger +2

This paper presents a novel model predictive control (MPC) approach for autonomous pick-and-place between moving platforms with a hook-equipped aerial manipulator. First, for accur…

eess.SY2026

Data-driven Learning of LPV Surrogate Models of Fuel Sloshing

E. Javier Olucha, Valentin Preda, Amritam Das +1

This paper aims to enhance the efficiency of validation and verification campaigns involving fuel sloshing phenomena. Our first contribution is the development of an open-source, h…

eess.SY2026

Data-driven augmentation of first-principles models under constraint-free well-posedness and stability guarantees

Bendegúz Györök, Roel Drenth, Chris Verhoek +3

The integration of first-principles models with learning-based components, i.e., model augmentation, has gained increasing attention, as it offers higher model accuracy and faster…

eess.SY2026

Learning Surrogate LPV State-Space Models with Uncertainty Quantification

E. Javier Olucha, Valentin Preda, Amritam Das +1

The Linear Parameter-Varying (LPV) framework enables the construction of surrogate models of complex nonlinear and high-dimensional systems, facilitating efficient stability and pe…