activity
20242026
collaborators

6 papers

math.OC2026

Model Predictive Control for Constrained Linear Positive Systems on Graphs

Roland Schurig, David Ohlin, Anders Rantzer +2

Positive systems describing networks with inherently non-negative states and inputs arise naturally in routing, logistics, and compartmental modelling. We consider problems modelle…

math.DS2026

On Data-Driven Unbiased Predictors using the Koopman Operator

Roland Schurig, Pieter van Goor, Karl Worthmann +1

The Koopman operator and its data-driven approximations, such as extended dynamic mode decomposition (EDMD), are widely used for analysing, modelling, and controlling nonlinear dyn…

math.DS2025

Shaping the Koopman dictionary by learning on the Grassmannian

Roland Schurig, Pieter van Goor, Karl Worthmann +1

Extended dynamic mode decomposition (EDMD) is a powerful tool to construct linear predictors of nonlinear dynamical systems by approximating the action of the Koopman operator on a…

eess.SY2025

Energy Aware and Safe Path Planning for Unmanned Aircraft Systems

Sebastian Gasche, Christian Kallies, Andreas Himmel +1

This paper proposes a path planning algorithm for multi-agent unmanned aircraft systems (UASs) to autonomously cover a search area, while considering obstacle avoidance, as well as…

eess.SY2025

A Modular Energy Aware Framework for Multicopter Modeling in Control and Planning Applications

Sebastian Gasche, Christian Kallies, Andreas Himmel +1

Unmanned aerial vehicles (UAVs), especially multicopters, have recently gained popularity for use in surveillance, monitoring, inspection, and search and rescue missions. Their man…

eess.SY2024

Geometric Data-Driven Dimensionality Reduction in MPC with Guarantees

Roland Schurig, Andreas Himmel, Rolf Findeisen

We address the challenge of dimension reduction in the discrete-time optimal control problem which is solved repeatedly online within the framework of model predictive control. Our…