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Items where Subject is "Institute of Vehicle Concepts > Vehicle System Dynamics and Control"

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Number of items at this level: 14.

  Ahmic, Kenan and Ultsch, Johannes and Brembeck, Jonathan and Burschka, Darius (2025) Multi-Agent Reinforcement Learning for Cooperative Vehicle Motion Control. In: 27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024. 27th IEEE International Conference on Intelligent Transportation Systems, 2024-09-24 - 2024-09-27, Edmonton, Kanada. doi: 10.1109/ITSC58415.2024.10920154. ISBN 979-833150592-9. ISSN 2153-0009. file

  Ahmic, Kenan and Ultsch, Johannes and Brembeck, Jonathan and Burschka, Darius (2025) Predictive Safeguarding and Performance Monitoring for Learning-based Vehicle Motion Controllers. In: 28th IEEE International Conference on Intelligent Transportation Systems, ITSC 2025. 28th IEEE International Conference on Intelligent Transportation Systems, ITSC 2025, 2025-11-18 - 2025-11-21, Gold Coast, Australien. Volltext nicht frei. file

  Baasch, Benjamin and Oselin, Pierfrancesco and Groos, Jörn Christoffer (2025) Ein digitaler Zwilling für die Analyse von dynamischen Fahrzeugreaktionen. SIGNAL + DRAHT, 117 (4), pp. 42-49. DVV Media Group. doi: 10.82268/eqyx-7d53. ISSN 0037-4997. file

  Brembeck, Jonathan and Tobolar, Jakub and de Castro, Ricardo (2025) VDCWorkbenchModels (Version 0.2.0). [Other] Volltext nicht online.

  Bünte, Tilman and Tobolar, Jakub (2025) Quasi-Periodic Feedforward Control based on Inverse Model tabled FFT. The 16th International Modelica & FMI Conference, 2025-09-08 - 2025-09-10, Luzern, Schweiz. doi: 10.3384/ecp218629. file

  Feistle, Friedrich and Kursawe, Martin and Lüdicke, Daniel and Sept, Jürgen (2024) OT-Security – Harmonisierter Bedrohungskatalog am Beispiel Schienenfahrzeuge. ZEVrail - Zeitschrift für das gesamte System Bahn, 148 (03), pp. 68-77. Georg Siemens Verlag. doi: 10.62682/VFTN3956. ISSN 1618-8330. file

  Heckmann, Andreas and Poßeckert, Alexander and Adusumalli, Vijaya-Bhaskar (2025) Aspects and Ideas for the FMI-based Modeling of Railway Digital Twins. Modelica Association and Linköping Electronic Conference Proceedings. Proceedings of 16th International Modelica & FMI Conference, 2025-09-08 - 2025-09-10, Lucerne, Switzerland. doi: 10.3384/ecp21891. file

  Hippmann, Gerhard and Blanco Mula, Blas (2025) Collaborative Digital Twin Development for Railway Braking and Traction Applications. Electronic press of Linköping Universitet. 16th International Modelica&FMI Conference, 2025-09-08 - 2025-09-10, Luzern, Schweiz. doi: 10.3384/ecp218101. ISSN 1650-3686. file

  Kamp, Tobias and Bürger, Christoff and Rein, Johannes and Brembeck, Jonathan (2025) Hybrid Simulation Models for Embedded Applications: A Modelica and eFMI approach. In: Proceedings of the 16th International Modelica&FMI Conference (218), pp. 545-555. 16th International Modelica & FMI Conference, 2025-09-08 - 2025-09-10, Lucerne, Switzerland. doi: 10.3384/ecp218555. ISBN 978-91-8118-266-8. ISSN 1650-3740. file

  Lies, Emily Kate (2025) Modeling and System Identification of a Scaled Railway Running Gear Test Rig with Independently Rotating Driven Wheels Based on Frequency Responses. Bachelor's, TU München. file

  Pfeiffer, Andreas and Winter, Christoph and Jarmolowitz, Fabian and Bertsch, Christian (2025) Optimization with FMI and CasADi: Analysis in Industrial Applications. In: Industrial User Presentations of 16th Modelica & FMI Conference. 16th International Modelica & FMI Conference, 2025-09-08 - 2025-09-10, Lucerne, Switzerland. file

  Posielek, Tobias (2026) Observer based Control for Railway Vehicles with Driven Independently Rotating Wheels Front-Rear Comparison on a 1:5 Scale Test Rig. IAVSD, 2026-08-18 - 2026-08-22, Shanghai. Volltext nicht frei. file

  Ruggaber, Julian and Pölzleitner, Daniel and Brembeck, Jonathan (2025) AI-Based Vehicle State Estimation Using Multi-Sensor Perception and Real-World Data. Sensors, 25 (14), p. 4253. Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/s25144253. ISSN 1424-8220. file

  Ultsch, Johannes and Ahmic, Kenan and Brembeck, Jonathan (2025) train_fmu_gym: A Functional Mock-up Unit-based Framework to Train Reinforcement Learning Agents for Multi-Physical Systems. IEEE Access. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/ACCESS.2025.3636787. ISSN 2169-3536. file

This list was generated on Fri Jan 16 20:36:06 2026 CET.
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