Our research focuses on the model & control design, analysis, and optimization of dynamical systems from different domains including robotics and human-machine interaction. It is also important for us to bring control and AI related research into practice by closely cooperating with industry, for instance from the automotive domain, robotics and process automation.
Research projects
Cooperative manipulation with dual-arm robots at the payload limit (headed bei Dr. Andreas Völz)
Kinesthetic teaching and predictive control of interaction tasks in robotics
Distributed model predictive control of nonlinear systems with asynchronous communication
Current projects
Energy-Efficient Electro-Photonic Integrated Circuits for High-Performance Computing
(Third Party Funds Group – Overall project)
Term: 1. April 2025 - 31. March 2028Funding source: Bayerische Forschungsstiftung
Prototypical development of an Aceton / Isopropanol hydrogen storage system for stationary seasonal energy storage
(Third Party Funds Single)
Term: 1. February 2025 - 31. March 2028Funding source: Helmholtz-Gemeinschaft
Advanced monitoring and optimization for robotic strain wave gears
(Third Party Funds Single)
Term: 1. November 2024 - 30. April 2026Funding source: Industrie
Receding horizon time-optimal path parameterization for robotic manipulators
(Third Party Funds Single)
Term: 1. July 2024 - 31. December 2025Funding source: Industrie
Optimized Reinforcement Architecture for Complex Energy Management
(Third Party Funds Single)
Term: 1. July 2024 - 30. June 2027Funding source: Industrie
Development of an innovative camera-based framework for collision-free human-machine movement
(Third Party Funds Single)
Term: 1. February 2024 - 31. January 2026Funding source: Bundesministerium für Wirtschaft und Energie (BMWE)
OXO-LOHC: Autotherme und ultratiefe Wasserstoff-Freisetzung aus LOHC
(Third Party Funds Single)
Term: 1. November 2023 - 31. October 2028Funding source: Helmholtz-Gemeinschaft
Model predictive flight control
(Third Party Funds Single)
Term: 1. August 2023 - 31. July 2026Funding source: Industrie
Robust energy-based control of MMC/HVDC systems
(Third Party Funds Single)
Term: 15. June 2023 - 31. December 2026Funding source: Industrie
Hardware architecture, automatic control, autonomy functionality, and developer community: Modular learning control and planning for mobile professional operation vehicles
(Third Party Funds Group – Sub project)
Overall project: POV.OS - Hardware and software platform for mobile professional operation vehiclesTerm: 1. January 2023 - 31. December 2025Funding source: Bundesministerium für Wirtschaft und Energie (BMWE)
Formulation of dispersed systems via (melt) emulsification: Process design, in situ diagnostics and regulation
(Third Party Funds Group – Sub project)
Overall project: Autonome Prozesse in der Partikeltechnik - Erforschung und Erprobung von Konzepten zur modellbasierten Führung partikeltechnischer ProzesseTerm: 1. January 2023 - 31. December 2025Funding source: DFG / Schwerpunktprogramm (SPP)
The aim of this project is the automated production of liquid-liquid disperse systems via melt emulsification, whereby in this process emulsification takes place at elevated temperature. The products obtained after cooling are dispersions of spherical nanoparticles or microparticles. Within the scope of this project, a melt emulsification device for the automated production of product particles with a well-defined particle size distribution (PSD) will be further developed. The PSD has a significant influence on the subsequent product properties, such as flow behavior or drug release kinetics. The PSD of the products is determined by the complex interaction of competing mechanisms. These are, in particular, droplet breakup in a rotor-stator device as a result of shear and elongation stress, as well as coalescence and further ripening, which in turn depend on the system composition, i.e. the emulsifier used (type, concentration) and the dispersion phase (viscosity, volume fraction). Therefore, for a better process understanding and an active process control, possibilities for in situ determination of the PSD are urgently required. In this project, a novel fiber-coupled measurement system based on broadband elastic light scattering is developed for in situ measurement of the PSD. The system will be validated on reference particle systems and applied to the emulsification process. Furthermore, a hybrid process model is developed, which is the basis for the design of a model predictive control of the process. The model predictive control in combination with the in situ measurement will provide the possibility for an active process control and the production of emulsions with predefined properties and a simultaneous optimization of the process time.
Predictive and learning control methods
(Third Party Funds Group – Sub project)
Overall project: AGENT-2: Agent-based data-driven modeling for stochastic and self-adjusting control of building energy systemsTerm: 1. November 2022 - 31. October 2025Funding source: Bundesministerium für Wirtschaft und Energie (BMWE)
To achieve climate targets, CO2 emissions in the building sector have to be significantly reduced. However, the integration of renewable energy sources increases the complexity of building energy systems and thus the requirements for the operation strategy. Model-based and predictive controllers are necessary for efficient operation. However, due to the high complexity of the energy systems, the development, implementation, and commissioning are very complex leading to high costs, which is why model predictive and optimization-based control strategies are rarely used in practice so far. The goal of the AGENT-2 project is to develop a self-adjusting and self-learning model-predictive control concept that reduces the implementation and commissioning effort and thus increases the applicability of efficient operating strategies in practice. The control concept to be developed is based on distributed agents, each of which learns the system behavior of a subsystem and controls the subsystem. This is based on the findings and the framework developed in the previous project AGENT. The operation of the overall system is achieved by the interaction oft h e self-learning agents with each other. Thus, a self-adjusting and scalable control strategy for building energy systems is created. The self-learning control strategy is compared with state-of-the-art concepts in simulations and tested in practical operation in two demonstration buildings. The findings will be generalized and possibilities for the transfer into practice will be investigated. The project thus contributes to increasing the efficiency of building operation and to reducing the costs of controller implementation and commissioning.
Robust Planning and Control using Probabilistic Methods
(Third Party Funds Group – Sub project)
Overall project: Verbundprojekt MANNHEIM-AUTOtech.agil: Architektur und Technologien zur Orchestrierung automobiltechnischer AgilitätTerm: 1. October 2022 - 30. September 2025Funding source: Bundesministerium für Forschung, Technologie und Raumfahrt (BMFTR)
Recent publications
2025
Conrad, P., Michalka, A., Beck, J., & Graichen, K. (2025). Nonlinear MPC for Stabilizing the Longitudinal Dynamics of a Highly Maneuverable Aircraft . In Proc. 2025 IEEE Aerospace Conference . Big Sky, Montana (USA).
Conrad, P., Steuter, L., Pierer von Esch, M., Beck, J., & Graichen, K. (2025). Aerodynamic neural network modeling for gradient-based model predictive flight control . In Proc. 33rd Mediterranean Conference on Control and Automation (MED 2025) .
Dio, M., Wahrburg, A., Enayati, N., Graichen, K., & Völz, A. (2025). Time-Optimal Path Parameterization with Viscous Friction and Jerk Constraints based on Reachability Analysis . In Proceedings of the 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . Hangzhou, CN.
Goller, T., Hopf, V., Völz, A., & Graichen, K. (2025). Fault Handling in Robotic Manipulation Tasks for Model Predictive Interaction Control . IEEE Robotics and Automation Letters , 10 (9), 9002 - 9009. https://doi.org/10.1109/LRA.2025.3592069
Hartmann, P., & Graichen, K. (2025). Learning-based uncertainty-aware predictive control of truck-trailer systems in rough terrain . In Institute of Electrical and Electronics Engineers (IEEE) (Eds.), Proceedings of the 19th IEEE International Conference on Control & Automation (ICCA) . Tallinn (Estonia), EE.
Kißkalt, J., Michalka, A., Strohmeyer, C., Horn, M., & Graichen, K. (2025). Estimation of input rotation speed in gauge-sensorized strain wave gears . In Proceedings of the 2025 IEEE Conference on Control Technology and Applications (CCTA) . San Diego (USA).
Kißkalt, J., Michalka, A., Strohmeyer, C., Horn, M., & Graichen, K. (2025). Model-based fault simulation and detection for gauge-sensorized strain wave gears . In IFAC-PapersOnLine (pp. 271 - 276). Vienna (Austria).
Kowalewski, J., Lorenz, A., Thomas, F., Valenzuela, R.A.A., & Graichen, K. (2025). Passivity-Based Robust Stability Analysis of the Converter–Grid Interaction and Passivity-Shaping Controller Design . IET Generation Transmission & Distribution , 19 (1). https://doi.org/10.1049/gtd2.70090
Kruse, T., Griebel, T., & Graichen, K. (2025). Adaptive Kalman filtering: Measurement and process noise covariance estimation using Kalman smoothing . IEEE Access , 13 , 11863-11875. https://doi.org/10.1109/ACCESS.2025.3528348
Landgraf, D., Völz, A., & Graichen, K. (2025). A software framework for stochastic model predictive control of nonlinear continuous-time systems (GRAMPC-S) . Optimization and Engineering . https://doi.org/10.1007/s11081-025-10006-z
Landgraf, D., Wietzke, T., & Graichen, K. (2025). Stochastic model predictive control with switched latent force models . European Journal of Control , 85 , 101311. https://doi.org/10.1016/j.ejcon.2025.101311
Pierer von Esch, M., Nistler, E., Völz, A., & Graichen, K. (2025). Sensitivity-based distributed NMPC: Experimental results for a levitating planar motion system . IEEE Transactions on Control Systems Technology . https://doi.org/10.1109/TCST.2025.3530165
Pierer von Esch, M., Völz, A., & Graichen, K. (2025). A fixed-point iteration scheme for sensitivity-based distributed optimal control . IEEE Transactions on Automatic Control , 70 (4), 2778-2785. https://doi.org/10.1109/TAC.2024.3505753
Pierer von Esch, M., Völz, A., & Graichen, K. (2025). Asynchronous sensitivity-based distributed optimal control for nonlinear systems . In Proceedings of the 2025 American Control Conference (ACC) . Denver, CO (USA).
Pierer von Esch, M., Völz, A., & Graichen, K. (2025). Sensitivity-Based Distributed Model Predictive Control for Nonlinear Systems under Inexact Optimization . Optimal Control Applications & Methods , (accepted) .
Rabenstein, G., Völz, A., & Graichen, K. (2025). Cable Manipulation for Contact Shaping Tasks using Elastic Rods . In Proceedings of the IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) . Portsmouth.
Santer, P., Reinhard, J., Schindler, A., & Graichen, K. (2025). Detection of localized bearing faults in PMSMs by means of envelope analysis and wavelet packet transform using motor speed and current signals . Mechatronics , 106 . https://doi.org/10.1016/j.mechatronics.2025.103294
Santer, P., Völz, A., & Graichen, K. (2025). A Model Predictive Control Approach to Trajectory Tracking with Human-Robot Collision Avoidance . In Proceedings of the 2025 IEEE Conference on Control Technology and Applications (CCTA) . San Diego, US.
Stecher, J., Kiltz, L., & Graichen, K. (2025). Generalized tolerance optimization for robust system design by adaptive learning of Gaussian processes . IEEE Access , (accepted) .
Südhoff, T., Hsuan-Yang, S., Villwock, J., Bliatsiou, C., Topalovic, D., Graichen, K.,... Knorn, S. (2025). Closed-loop control of a liquid-liquid mixer using MPC and GPR-models . In Proceedings of the 33rd Mediterranean Conference on Control and Automation (MED 2025) . Tangier, Morocco, MA.
Ullrich, L., Buchholz, M., Dietmayer, K., & Graichen, K. (2025). Expanding the Classical V-Model for the Development of Complex Systems Incorporating AI . IEEE Transactions on Intelligent Vehicles , 10 (3), 1790-1804. https://doi.org/10.1109/TIV.2024.3434515
Ullrich, L., Buchholz, M., Petit, J., Dietmayer, K., & Graichen, K. (2025). A Concept for Efficient Scalability of Automated Driving Allowing for Technical, Legal, Cultural, and Ethical Differences . In Proceedings of the 2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC) . Gold Coast (Australia).
Ullrich, L., Mujirishvili, Z., & Graichen, K. (2025). Enhancing system self-awareness and trust of AI: A case study in trajectory prediction and planning . In Proceedings of the 36th IEEE Intelligent Vehicles Symposium (IEEE IV 2025) . Cluj-Napoca (Romania).
Ullrich, L., Zimmer, W., Greer, R., Graichen, K., Knoll, A.C., & Trivedi, M. (2025). A New Perspective On AI Safety Through Control Theory Methodologies . IEEE Open Journal of Intelligent Transportation Systems , 6 , 938-966. https://doi.org/10.1109/OJITS.2025.3585274
Wietzke, T., & Graichen, K. (2025). Physics-informed sparse Gaussian processes for model predictive control in building energy systems . In IFAC-PapersOnLine (pp. 43-48). Vienna (Austria).
Wietzke, T., Landgraf, D., & Graichen, K. (2025). Application of stochastic model predictive control for building energy systems using latent force models . At-Automatisierungstechnik , 73 (6), 441-450. https://doi.org/10.1515/auto-2024-0160
2024
Cherian, A.J., Michalka, A., Murray, K., Roell, G., & Graichen, K. (2024). Control approaches for operating point stabilization of microring resonator modulators under fast perturbations . In Graham T. Reed, Andrew P. Knights (Eds.), Proceedings Silicon Photonics XIX (pp. 128910D). SPIE.
Conrad, P., & Graichen, K. (2024). A sensitivity-based approach to self-triggered nonlinear model predictive control . IEEE Access , 12 , 153243-153252. https://doi.org/10.1109/ACCESS.2024.3480522
Dahlmann, J., Graichen, K., & Völz, A. (2024). Ein Konzept zum automatisierten Rangieren von Fahrzeugen mit Anhängern .
Dahlmann, J., Völz, A., Lukassek, M., & Graichen, K. (2024). Local predictive optimization of globally planned motions for truck-trailer systems . IEEE Transactions on Control Systems Technology , 32 (5), 1555-1568. https://doi.org/10.1109/TCST.2023.3345169
Dio, M., Graichen, K., & Völz, A. (2024). Time-Optimal Path Parameterization for Cooperative Multi-Arm Robotic Systems with Third-Order Constraints . In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 3043-3048). Abu Dhabi, AE: Institute of Electrical and Electronics Engineers Inc..
Goller, T., Brohm, D., Völz, A., & Graichen, K. (2024). DMP-based path planning for model predictive interaction control . In Proceedings of the European Control Conference (pp. 128-133). Stockholm (Sweden).
Goller, T., Völz, A., & Graichen, K. (2024). A Programming by Demonstration Approach for Robotic Manipulation with Model Predictive Interaction Control . In Proceedings of the 2024 IEEE Conference on Control Technology and Applications (CCTA) (pp. 799-804). Newcastle upon Tyne, United Kingdom.
Goppelt-Schneider, F., Schmidt-Vollus, R., & Graichen, K. (2024). Trajectory tracking control for multilevel pressure boosting systems . In Proceedings of the 28th International Conference on System Theory, Control and Computing (ICSTCC) . Sinaia, Romania.
Kißkalt, J., Michalka, A., Strohmeyer, C., Horn, M., & Graichen, K. (2024). Fault detection in gauge-sensorized strain wave gears . In Proceedings of the European Control Conference (pp. 26-33). Stockholm (Sweden).
Kögler, P., Dahlmann, J., & Graichen, K. (2024). Side-Slip Compensation in Model Predictive Path Following Control for General-n-Trailer Systems . In Proceedings of the 28th International Conference on System Theory, Control and Computing (ICSTCC) . Sinaia, Romania.
Lukassek, M., Dahlmann, J., Völz, A., & Graichen, K. (2024). Model predictive path-following control for truck–trailer systems with specific guidance points - Design and experimental validation . Mechatronics , 100 , 103190. https://doi.org/10.1016/j.mechatronics.2024.103190
Löhe, K., Reinhard, J., Petrasch, N., Kallabis, S., Graichen, K., & Mucha, M. (2024). Work Roll Speed Drop Compensation for Hot Strip Mills Reduces Drivetrain Wear and Increases Strip Quality . In AISTech 2024 — Proceedings of the Iron & Steel Technology Conference (pp. 1212-1223). Columbus, OH, US: Warrendale, PA: Association for Iron and Steel Technology.
Pierer von Esch, M., Landgraf, D., Steffel, M., Völz, A., & Graichen, K. (2024). Distributed Stochastic Optimal Control of Nonlinear Systems based on ADMM . IEEE Control Systems Letters , 8 , 424-429. https://doi.org/10.1109/LCSYS.2024.3393411
Pierer von Esch, M., Völz, A., & Graichen, K. (2024). Asynchronous ADMM for Nonlinear Continuous-Time Systems . Optimal Control Applications & Methods .
Pierer von Esch, M., Völz, A., & Graichen, K. (2024). Sensitivity-Based Distributed Model Predictive Control: Synchronous and Asynchronous Execution Compared to ADMM . At-Automatisierungstechnik , 72 (2), 91-106. https://doi.org/10.1515/auto-2023-0050
Rabenstein, G., Ullrich, L., & Graichen, K. (2024). Sampling for model predictive trajectory planning in autonomous driving using normalizing flows . In Proc. 35th IEEE Intelligent Vehicles Symposium (IEEE IV 2024) (pp. 2091-2096). Jeju Island (Korea).
Reinhard, J., Löhe, K., & Graichen, K. (2024). Optimal dynamic current control for externally excited synchronous machines . In Proceedings of the 2024 IEEE Conference on Control Technology and Applications (CCTA) (pp. 146-152). Newcastle upon Tyne, UK.
Reinhard, J., Löhe, K., Petrasch, N., Kallabis, S., & Graichen, K. (2024). Dynamic compensation of the threading speed drop in rolling processes . Journal of Process Control , 137 , 103197. https://doi.org/10.1016/j.jprocont.2024.103197
Schumann, M., & Graichen, K. (2024). PINN-based dynamical modeling and state estimation in power inverters . In Proceedings of the 2024 IEEE Conference on Control Technology and Applications (CCTA) . Newcastle upon Tyne, UK.
Snobar, F., Michalka, A., Horn, M., Strohmeyer, C., & Graichen, K. (2024). Sensitivity-based moving horizon estimation of road friction . In Proceedings of the European Control Conference (pp. 718-724). Stockholm (Sweden).
Südhoff, T., Ebner, L., Schmidt, J., & Graichen, K. (2024). GP-based modeling for PSD control of emulsification processes . In Proceedings of the 28th International Conference on System Theory, Control and Computing (ICSTCC) . Sinaia, Romania.
Ullrich, L., Buchholz, M., Dietmayer, K., & Graichen, K. (2024). AI safety assurance for automated vehicles: A survey on research, standardization, regulation . IEEE Transactions on Intelligent Vehicles . https://doi.org/10.1109/TIV.2024.3496797
Ullrich, L., McMaster, A., & Graichen, K. (2024). Transfer learning study of motion transformer based trajectory predictions . In Proc. 35th IEEE Intelligent Vehicles Symposium (IEEE IV 2024) (pp. 110-117). Jeju Island (Korea).
Verhoolen, A., Geißelbrecht, M., Kadar, J., Preuster, P., Wasserscheid, P., & Graichen, K. (2024). Bayesian optimization of operating points of a continuous perhydro-dibenzyltoluene dehydrogenation reactor . International Journal of Energy Research . https://doi.org/10.1155/2024/5627453
Wietzke, T., Gall, J., & Graichen, K. (2024). Occupancy Prediction for Building Energy Systems with Latent Force Models . Energy and Buildings , 113968. https://doi.org/10.1016/j.enbuild.2024.113968
2023
Dio, M., Demir, O., Trachte, A., & Graichen, K. (2023). Safe active learning and probabilistic design of experiment for autonomous hydraulic excavators . In Proceedings of the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 9685-9690). Detroit, US.
Dio, M., Völz, A., & Graichen, K. (2023). Cooperative dual-arm control for heavy object manipulation based on hierarchical quadratic programming . In Proceedings of the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 643-648). Detroit, US.
Frank, R., Wittmann, L.-M., Kleffel, T., Roth, B., Graichen, K., & Drummer, D. (2023). Investigating the Integration of Nonwoven Carbon Fibers for Mechanical Enhancement in Compression Molded Fiber-Reinforced Polymer Bipolar Plates . Polymers , 15 (19). https://doi.org/10.3390/polym15193891
Geiling, J., Wagner, L., Auer, F., Ortner, F., Nuß, A., Seyfried, R.,... Preuster, P. (2023). Operational experience with a liquid organic hydrogen carrier (LOHC) system for bidirectional storage of electrical energy over 725 h . Journal of Energy Storage , 72 . https://doi.org/10.1016/j.est.2023.108478
Gold, T., Völz, A., & Graichen, K. (2023). Model predictive interaction control for robotic manipulation tasks . IEEE Transactions on Robotics , 39 (1), 76-89. https://doi.org/10.1109/TRO.2022.3196607
Harder, K., Niemeyer, J., Remele, J., & Graichen, K. (2023). Hierarchical model predictive control for an off-highway Diesel engine with SCR catalyst . International Journal of Engine Research . https://doi.org/10.1177/14680874221143600
Hoffmann, M., Braun, S., Sura, O., Stelzig, M., Schüßler, C., Graichen, K., & Vossiek, M. (2023). Concept for an Automatic Annotation of Automotive Radar Data Using AI-segmented Aerial Camera Images . In Proceedings of the IEEE Radar Conference . Sydney, NSW, AU: Institute of Electrical and Electronics Engineers Inc..
Kißkalt, J., Michalka, A., Strohmeyer, C., Horn, M., & Graichen, K. (2023). Simulation chain for sensorized strain wave gears . In Proc. 27th International Conference on System Theory, Control and Computing (ICSTCC) (pp. 467 - 473). Timisoara (Romania).
Landgraf, D., Völz, A., Berkel, F., Schmidt, K., Specker, T., & Graichen, K. (2023). Probabilistic prediction methods for nonlinear systems with application to stochastic model predictive control . Annual Reviews in Control , 56 , 100905. https://doi.org/10.1016/j.arcontrol.2023.100905
Rohrmüller, M., Beckerle, P., Graichen, K., Malvezzi, M., & Pozzi, M. (2023). In-Hand Manipulation with Synergistic Actuated Robotic Hands: An MPC-Based Approach . In 2023 IEEE-RAS 22nd International Conference on Humanoid Robots (Humanoids) . Austin, TX, US: IEEE Computer Society.
Schumann, M., Ebersberger, S., & Graichen, K. (2023). Improved nonlinear estimation in thermal networks using machine learning . In Proc. IEEE International Conference on Mechatronics (ICM 2023, accepted) . Loughborough (UK).
Schumann, M., Ebersberger, S., & Graichen, K. (2023). Online learning and adaptation of nonlinear thermal networks for power inverters . In Proceedings of the 49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023) . Marina Bay Sands (Singapore).
Snobar, F., Michalka, A., Horn, M., Strohmeyer, C., & Graichen, K. (2023). Rack force estimation from standstill to high speeds by hybrid model design and blending . In Proceedings of the IEEE International Conference on Mechatronics (ICM 2023) . Loughborough (UK).
Spenger, P., & Graichen, K. (2023). Performance prediction of NMPC algorithms with incomplete optimization . In Proc. 22nd IFAC World Congress (accepted) (pp. 7456-7461). Yokohama, Japan.
Ullrich, L., Völz, A., & Graichen, K. (2023). Robust meta-learning of vehicle yaw rate dynamics via conditional neural processes . In Proc. 62nd IEEE Conference on Decision and Control (CDC) (pp. 322-327). Marina Bay Sands (Singapore).
2022
Bergmann, D., Harder, K., Niemeyer, J., & Graichen, K. (2022). Nonlinear MPC of a Heavy-Duty Diesel Engine With Learning Gaussian Process Regression . IEEE Transactions on Control Systems Technology , 30 (1), 113-129. https://doi.org/10.1109/TCST.2021.3054650
Burk, D., Völz, A., & Graichen, K. (2022). A modular framework for distributed model predictive control of nonlinear continuous-time systems (GRAMPC-D) . Optimization and Engineering , 23 , 771-795. https://doi.org/10.1007/s11081-021-09605-3
Burk, D., Völz, A., & Graichen, K. (2022). Improving the performance of distributed model predictive control by applying graph partitioning methods . In Proceedings of the 26th International Conference on System Theory, Control and Computing (ICSTCC) . Sinaia (Romania).
Dahlmann, J., Völz, A., Szabo, T., & Graichen, K. (2022). A Numerical Approach for Solving the Inversion Problem for n-Trailer Systems . In 2022 American Control Conference (ACC) (pp. 2018-2024). Atlanta, GA, US: Institute of Electrical and Electronics Engineers Inc..
Dahlmann, J., Völz, A., Szabo, T., & Graichen, K. (2022). Trajectory optimization for truck-trailer systems based on predictive path-following control . In Proceedings of the 6th IEEE Conference on Control Technology and Applications (CCTA) . Trieste (Italy).
Gold, T., Römer, R., Völz, A., & Graichen, K. (2022). Catching objects with a robot arm using model predictive control . In Proceedings 2022 American Control Conference (ACC) (pp. 1915-1920). Atlanta, GA (USA).
Goller, T., Gold, T., Völz, A., & Graichen, K. (2022). Model predictive interaction control based on a path-following formulation . In Proceedings IEEE International Conference on Mechatronics and Automation (ICMA) (pp. 551-556). Guilin (China).
Graichen, K., & Görges, D. (2022). Ausgewählte Beiträge des GMA Fachausschusses 1.50 .,Grundlagen vernetzter Systeme" . At-Automatisierungstechnik , 70 (4), 315-316. https://doi.org/10.1515/auto-2022-0033
Huber, H., Burk, D., & Graichen, K. (2022). Comparison of sensitivity-based and ADMM-based DMPC applied to building automation . In Proceedings of the 6th IEEE Conference on Control Technology and Applications (CCTA) (pp. 546-553). Trieste (Italy).
Kowalewski, J., Lorenz, A., Lomakin, A., Alvarez, R., & Graichen, K. (2022). Circulating current control and energy balancing of a modular multilevel converter using model predictive control for HVDC applications . In Proceedings of the 48th Annual Conference of the IEEE Industrial Electronics Society (IECON 2022) . Brussels (BE).
Lamprecht, A., Steffen, D., Nagel, K., Häcker, J., & Graichen, K. (2022). Online Model Predictive Motion Cueing With Real-Time Driver Prediction . IEEE Transactions on Intelligent Transportation Systems , 23 (8), 12414-12428. https://doi.org/10.1109/tits.2021.3114003
Landgraf, D., Völz, A., & Graichen, K. (2022). Nonlinear model predictive control with latent force models . In Proceedings 2022 American Control Conference (ACC) (pp. 4979-4984). Atlanta, GA (USA).
Landgraf, D., Völz, A., Kontes, G., Graichen, K., & Mutschler, C. (2022). Hierarchical learning for model predictive collision avoidance . In IFAC PapersOnLine (pp. 355-360). Vienna (Austria).
Makowicki, T., Bitzer, M., & Graichen, K. (2022). Cycle-by-Cycle Combustion Optimisation: Calibration of Data-based Models and Improvements of Computational Efficiency . Mathematical and Computer Modelling of Dynamical Systems , (accepted) . https://doi.org/10.1080/13873954.2022.2052111
Rabenstein, G., Demir, O., Trachte, A., & Graichen, K. (2022). Data-driven feed-forward control of hydraulic cylinders using Gaussian process regression for excavator assistance functions . In Proceedings of the 6th IEEE Conference on Control Technology and Applications (CCTA) (pp. 962-969). Trieste (Italy).
Reinhard, J., Löhe, K., & Graichen, K. (2022). Optimal current setpoint computation for externally excited synchronous machines . In Proceedings of the 6th IEEE Conference on Control Technology and Applications (CCTA) (pp. 1319-1326). 6th IEEE Conference on Control Technology and Applications (CCTA).
Schumann, M., Ebersberger, S., & Graichen, K. (2022). Dynamic and stationary state estimation of fluid cooled three-phase inverters . In Proceedings of the 26th IEEE International Symposium on Power Electronics, Electrical Drives Automation and Motion (SPEEDAM 2022) . Sorrento (Italy).
Snobar, F., Reinhard, J., Huber, H., Hoffmann, M., Stelzig, M., Vossiek, M., & Graichen, K. (2022). FOV-based model predictive object tracking for quadcopters . In Proceedings of the 9th IFAC Symposium on Mechatronic Systems (Mechatronics 2022) (pp. 13 - 18). Los Angeles, CA (USA).
Stecher, J., Kiltz, L., & Graichen, K. (2022). Semi-infinite programming using Gaussian process regression for robust design optimization . In Proceedings European Control Conference (pp. 52-59). London (UK).
2021
Burk, D., Völz, A., & Graichen, K. (2021). Experimental validation of the open-source DMPC framework GRAMPC-D applied to the remote-accessible robotarium . In Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA) .
Burk, D., Völz, A., & Graichen, K. (2021). Towards asynchronous ADMM for distributed model predictive control of nonlinear systems . In Proceedings European Control Conference (ECC 2021) (pp. 1950-1955).
Gold, T., Rohrmüller, M., Völz, A., & Graichen, K. (2021). Model predictive interaction control for force closure grasping . In Proceedings of the 2021 IEEE Conference on Decision and Control (CDC) (pp. 1018-1023). Austin, TX, USA.
Huber, H., & Graichen, K. (2021). A sensitivity-based distributed model predictive control algorithm for nonlinear continuous-time systems . In 5th IEEE Conference on Control Technology and Applications (CCTA) (pp. (accepted)).
Lamprecht, A., Emmert, T., & Graichen, K. (2021). Learning-based driver prediction for MPC-based motion cueing algorithms . In Driving Simulation Conference Europe 2021 (DSC) (pp. 133 - 140).
Lamprecht, A., Steffen, D., Häcker, J., & Graichen, K. (2021). Potential der modellprädiktiven Regelung für Fahrsimulatoren . At-Automatisierungstechnik , 69 (2), 155-170. https://doi.org/10.1515/auto-2020-0090
Lukassek, M., Völz, A., Szabo, T., & Graichen, K. (2021). Model predictive path-following control for general n-trailer systems with an arbitrary guidance point . In Proceedings European Control Conference (ECC 2021) (pp. 1329-1334).
Völz, A., & Graichen, K. (2021). Gradient-based nonlinear model predictive control for systems with state-dependent mass matrix . In Proceedings of the 2021 IEEE Conference on Decision and Control (CDC), accepted .
2020
Bergmann, D., & Graichen, K. (2020). Safe Bayesian Optimization under Unknown Constraints . In 59th IEEE Conference on Decision and Control (CDC 2020) (pp. 3592-3597). Institute of Electrical and Electronics Engineers Inc..
Burk, D., Völz, A., & Graichen, K. (2020). Distributed optimization with ALADIN for non-convex optimal control problems . In 59th IEEE Conference on Decision and Control (CDC 2020) .
Burk, D., Völz, A., & Graichen, K. (2020). Neighbor approximations for distributed optimal control of nonlinear networked systems . In Proceedings of the European Control Conference (ECC 2020) (pp. 1238-1243).
Englert, T., & Graichen, K. (2020). Nonlinear model predictive torque control and setpoint computation of induction machines for high performance applications . Control Engineering Practice , 99 . https://doi.org/10.1016/j.conengprac.2020.104415
Geiselhart, R., Bergmann, D., Niemeyer, J., Remele, J., & Graichen, K. (2020). Hierarchical Predictive Control of a Combined Engine/Selective Catalytic Reduction System with Limited Model Knowledge . SAE International Journal of Engines , 13 (2), 211-222. https://doi.org/10.4271/03-13-02-0015
Gold, T., Lomakin, A., Goller, T., Völz, A., & Graichen, K. (2020). Towards a Generic Manipulation Framework for Robots based on Model Predictive Interaction Control . In Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA) (pp. 401 - 407). Beijing, CN.
Gold, T., Völz, A., & Graichen, K. (2020). Model Predictive Interaction Control for Industrial Robots . In Proceedings of the 21st IFAC World Congress (pp. 10026 - 10033). Berlin, DE.
Gold, T., Völz, A., & Graichen, K. (2020). Model Predictive Position and Force Trajectory Tracking Control for Robot-Environment Interaction . In Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 7397-7402). Las Vegas, NV, USA, US.
Jemaa, K., Kotman, P., Reimann, S., & Graichen, K. (2020). Tube-based internal model control of minimum-phase input-affine MIMO systems under input constraints . In Proceedings of the 21st IFAC World Congress .
Joos, S., Trachte, A., Bitzer, M., & Graichen, K. (2020). Constrained real-time control of hydromechanical powertrains - methodology and practical application . Mechatronics , 71 . https://doi.org/10.1016/j.mechatronics.2020.102397
Kruse, T., & Graichen, K. (2020). Moving horizon estimation for continuous glucose monitoring . In Proceedings of the 7th International Conference on Biomedical Engineering and Systems (ICBES 20) .
Lomakin, A., Mayr, A., Graichen, K., & Franke, J. (2020). Optimization of direct winding processes based on a holistic control approach . In Proceedings of the Electric Drives Production Conference (E-DPC) . Ludwigsburg (D).
Lukassek, M., Völz, A., Szabo, T., & Graichen, K. (2020). Model predictive control for agricultural machines with implements . In Proceedings 28th Mediterranean Conference on Control and Automation (MED) (pp. 387-392).
Mayr, A., Kißkalt, D., Lomakin, A., Graichen, K., & Franke, J. (2020). Towards an intelligent linear winding process through sensor integration and machine learning techniques . In Proceedings of the 8th CIRP Global Web Conference – Flexible Mass Customisation (CIRPe 2020) .
Mesmer, F., Szabo, T., & Graichen, K. (2020). Learning feedforward control of a hydraulic clutch actuation path based on policy gradients . In 59th IEEE Conference on Decision and Control (CDC 2020) .
Völz, A., & Graichen, K. (2020). Prädiktive Pfadfolgeregelung für die kollisionsfreie Bewegungsplanung von Robotern . At-Automatisierungstechnik , 68 (7), 557-570. https://doi.org/10.1515/auto-2020-0048
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Our research focuses on the model & control design, analysis, and optimization of dynamical systems from different domains including robotics and human-machine interaction. It is also important for us to bring control and AI related research into practice by closely cooperating with industry, for instance from the automotive domain, robotics and process automation.
Research projects
Energy-Efficient Electro-Photonic Integrated Circuits for High-Performance Computing
(Third Party Funds Group – Overall project)
Funding source: Bayerische Forschungsstiftung
Prototypical development of an Aceton / Isopropanol hydrogen storage system for stationary seasonal energy storage
(Third Party Funds Single)
Funding source: Helmholtz-Gemeinschaft
Advanced monitoring and optimization for robotic strain wave gears
(Third Party Funds Single)
Funding source: Industrie
Receding horizon time-optimal path parameterization for robotic manipulators
(Third Party Funds Single)
Funding source: Industrie
Optimized Reinforcement Architecture for Complex Energy Management
(Third Party Funds Single)
Funding source: Industrie
Development of an innovative camera-based framework for collision-free human-machine movement
(Third Party Funds Single)
Funding source: Bundesministerium für Wirtschaft und Energie (BMWE)
OXO-LOHC: Autotherme und ultratiefe Wasserstoff-Freisetzung aus LOHC
(Third Party Funds Single)
Funding source: Helmholtz-Gemeinschaft
Model predictive flight control
(Third Party Funds Single)
Funding source: Industrie
Robust energy-based control of MMC/HVDC systems
(Third Party Funds Single)
Funding source: Industrie
Hardware architecture, automatic control, autonomy functionality, and developer community: Modular learning control and planning for mobile professional operation vehicles
(Third Party Funds Group – Sub project)
Term: 1. January 2023 - 31. December 2025
Funding source: Bundesministerium für Wirtschaft und Energie (BMWE)
Formulation of dispersed systems via (melt) emulsification: Process design, in situ diagnostics and regulation
(Third Party Funds Group – Sub project)
Term: 1. January 2023 - 31. December 2025
Funding source: DFG / Schwerpunktprogramm (SPP)
Predictive and learning control methods
(Third Party Funds Group – Sub project)
Term: 1. November 2022 - 31. October 2025
Funding source: Bundesministerium für Wirtschaft und Energie (BMWE)
Robust Planning and Control using Probabilistic Methods
(Third Party Funds Group – Sub project)
Term: 1. October 2022 - 30. September 2025
Funding source: Bundesministerium für Forschung, Technologie und Raumfahrt (BMFTR)
2025
2024
2023
2022
2021
2020
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