Department of Mathematics
Chair of Applied Mathematics

M.Sc. Jonas Schießl

• project member
• Room: 3.2 01 530 (NW II)
• e-mail: Jonas.Schiessl@uni-bayreuth.de

project: “Stochastic Optimal Control and MPC – Dissipativity, Risk and Performance”

software: nMPyC (python package for solving optimal control problems via MPC)

Department of Mathematics
Chair of Applied Mathematics

• Model Predictive Control
• Stochastic Systems
• Systems and Control Theory

Department of Mathematics
Chair of Applied Mathematics

Publications

Articles (reviewed)    

Ruchuan Ou, Learta Januzi, Jonas Schießl, Michael Heinrich Baumann, Lars Grüne and Timm Faulwasser: PolyOCP.jl : A Julia Package for Stochastic OCPs and MPC. In: European Journal of Control, (2026). - 101617.
doi:10.1016/j.ejcon.2026.101617

Jonas Schießl, Michael Heinrich Baumann, Timm Faulwasser and Lars Grüne: On the relationship between stochastic turnpike and dissipativity notions. In: IEEE Transactions on Automatic Control, 70 (2025). - S. 3527-3539.
doi:10.1109/TAC.2024.3504352

Ruchuan Ou, Jonas Schießl, Michael Heinrich Baumann, Lars Grüne and Timm Faulwasser: A polynomial chaos approach to stochastic LQ optimal control : Error bounds and infinite-horizon results. In: Automatica, 174 (2025). - 112117.
doi:10.1016/j.automatica.2025.112117

Jonas Schießl, Ruchuan Ou, Timm Faulwasser, Michael Heinrich Baumann and Lars Grüne: Turnpike and Dissipativity in Generalized Discrete-Time Stochastic Linear-Quadratic Optimal Control. In: SIAM Journal on Control and Optimization, 63 (2025). - S. 1432-1457.
doi:10.1137/23M160089X

Gabriele Eichfelder, Lars Grüne, Lisa Krügel and Jonas Schießl: Relaxed dissipativity assumptions and a simplified algorithm for multiobjective MPC. In: Computational Optimization and Applications, 86 (2023). - S. 1081-1116.
doi:10.1007/s10589-022-00398-4

Conference Proceedings (reviewed)    

Jonas Schießl, Ruchuan Ou, Michael Heinrich Baumann, Timm Faulwasser and Lars Grüne: Towards turnpike-based performance analysis of risk-averse stochastic predictive control. In: 2025 IEEE 64th Conference on Decision and Control (CDC) : Proceedings. - Rio de Janeiro, Brazil : 2025. - S. 329-335.
doi:10.1109/CDC57313.2025.11312994

Jonas Schießl, Ruchuan Ou, Timm Faulwasser, Michael Heinrich Baumann and Lars Grüne: Near-optimal performance of stochastic economic MPC. In: 2024 IEEE 63rd Conference on Decision and Control (CDC) : Proceedings. - Milan, Italy : 2024. - S. 2565-2571.
doi:10.1109/CDC56724.2024.10886281

Jonas Schießl, Ruchuan Ou, Timm Faulwasser, Michael Heinrich Baumann and Lars Grüne: Pathwise turnpike and dissipativity results for discrete-time stochastic linear-quadratic optimal control problems. In: 2023 62nd IEEE Conference on Decision and Control (CDC). - Piscataway, NJ : IEEE, 2023. - S. 2790-2795.
doi:10.1109/CDC49753.2023.10384081

Articles, Proceedings and Book Chapters (non-reviewed)    

Jonas Schießl and Lisa Krügel: nMPyC A Python Package for Solving Optimal Control Problems via Model Predictive Control. In: Aris Daniilidis, Lars Grüne, Josef Haunschmied, Gernot Tragler (Hrsg.): Model Predictive Control : Engineering Methods for Economists. - Cham, Switzerland : Springer, 2025. - S. 111-133.
doi:10.1007/978-3-031-85256-5_5

Working Papers & Preprints    

Jonas Schießl, Ruchuan Ou, Michael Heinrich Baumann, Timm Faulwasser and Lars Grüne: Closed-loop analysis of linear stochastic MPC with risk-averse constraints.. - Bayreuth, 2026-04-13. - 8 S.
doi:10.48550/arXiv.2604.11183

Jonas Schießl, Hannah Selder, Ruchuan Ou, Michael Heinrich Baumann, Timm Faulwasser and Lars Grüne: Stability and performance of stochastic economic MPC : Stochastic characterization of the closed-loop asymptotics.. - Bayreuth, 2025-10-22. - 36 S.
doi:10.48550/arXiv.2510.19416

Department of Mathematics
Chair of Applied Mathematics

M.Sc. Jonas Schießl
from 10/2022 on: project member

Chair of Applied Mathematics
Department of Mathematics
University of Bayreuth
95440 Bayreuth, Germany

Room Number: 3.2 01 530

Building: NW II

Phone: +49 (0)921 55-3278
E-mail: Jonas.Schiessl@uni-bayreuth.de