Schurig, Roland ; Himmel, Andreas ; Findeisen, Rolf (2024)
Geometric Data-Driven Dimensionality Reduction in MPC with Guarantees.
22nd European Control Conference. Stockholm, Sweden (25.06.2024-28.06.2024)
doi: 10.23919/ECC64448.2024.10591254
Konferenzveröffentlichung, Bibliographie

Himmel, Andreas ; Matschek, Janine ; Kok (Louis), Rudolph ; Morabito, Bruno ; Nguyen, Hoang Hai ; Findeisen, Rolf
Hrsg.: Soroush, Masoud ; Braatz, Richard D. (2024)
Machine learning for control of (bio)chemical manufacturing systems.
In: Artificial Intelligence in Manufacturing - Concepts and Methods
doi: 10.1016/B978-0-323-99134-6.00009-8
Buchkapitel, Bibliographie

Schurig, Roland ; Himmel, Andreas ; Findeisen, Rolf (2023)
Geometric Data-Driven Dimensionality Reduction in MPC with Guarantees.
doi: 10.48550/arXiv.2312.02734
Report, Bibliographie

Häusser, Felix ; Himmel, Andreas ; Karvinen, Kai S. ; Findeisen, Rolf (2023)
Data-driven Adaptive Surface Control for Automated Directional Drilling.
2023 IEEE Conference on Control Technology and Applications. Bridgetown, Barbados (16.08.2023-18.08.2023)
doi: 10.1109/CCTA54093.2023.10252434
Konferenzveröffentlichung, Bibliographie

Schurig, Roland ; Himmel, Andreas ; Mešanović, Amer ; Braatz, Richard D. ; Findeisen, Rolf (2023)
Estimating Parameter Regions for Structured Parameter Tuning via Reduced Order Subsystem Models.
2023 American Control Conference. San Diego, USA (31.05.2023 - 02.06.2023)
doi: 10.23919/ACC55779.2023.10156542
Konferenzveröffentlichung, Bibliographie

Schurig, Roland ; Himmel, Andreas ; Findeisen, Rolf (2023)
Towards Grassmannian Dimensionality Reduction in MPC.
In: IEEE Control Systems Letters, 7
doi: 10.1109/LCSYS.2023.3291229
Artikel, Bibliographie

Häusser, Felix ; Himmel, Andreas ; Findeisen, Rolf (2023)
Data-driven adaptive two-degree of freedom control of interconnected systems for reference tracking.
In: IFAC-PapersOnLine, 56 (2)
doi: 10.1016/j.ifacol.2023.10.1367
Artikel, Bibliographie

Himmel, Andreas ; Findeisen, Rolf ; Sundmacher, Kai (2022)
Closed-loop real-time optimization for unsteady operating production systems.
In: Journal of Process Control, 113
doi: 10.1016/j.jprocont.2022.03.002
Artikel, Bibliographie