C05: Stochastic port-Hamiltonian systems and applications to stochastic optimal control
Principal investigators:
Prof. Dr. Matthias Ehrhardt; Prof. Dr. Thomas Kruse
Project description:
In order to systematically integrate stochastic influences such as random noise into the port-Hamiltonian formalism, a novel approach is developed that extends Dirac structures by a stochastic component. This offers the possibility to develop more realistic models and at the same time to obtain a stochastic dissipativity inequality. Subsequently, optimal control problems for stochastic port-Hamiltonian systems are treated and strategies are derived that control these systems optimally into desired configurations.
Researchers:
Publications of project C05:
4.
Ackermann, Julia; Ehrhardt, Matthias; Kruse, Thomas; Tordeux, Antoine
Modelling car-following dynamics with stochastic input-state-output port-Hamiltonian systems
EPJ Web Conf., 334 : 03009
20253.
Di Persio, Luca; Ehrhardt, Matthias; Outaleb, Youness; Rizzotto, Sofia
Port-Hamiltonian Neural Networks: From Theory to Simulation of Interconnected Stochastic Systems
arXiv preprint arXiv:2509.06674
20252.
Ackermann, Julia; Ehrhardt, Matthias; Kruse, Thomas; Tordeux, Antoine
Stabilisation of stochastic single-file dynamics using port-Hamiltonian systems
IFAC-PapersOnLine, 58 (17) :145—150
2024
Herausgeber: Elsevier1.
Ehrhardt, Matthias; Kruse, Thomas; Tordeux, Antoine
The collective dynamics of a stochastic port-Hamiltonian self-driven agent model in one dimension
ESAIM: Mathematical Modelling and Numerical Analysis, 58 (2) :515—544
2024
Herausgeber: EDP Sciences
