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Systems and Control division focusing on data-driven control methodologies. About the research project Model-based control is arguably the prime framework to perform certifiably-safe regulation of dynamical
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to the lack of generation inertia worsening power system stability. Control of such a complex system relies on detailed understanding and real-time modelling of the nonlinear dynamics resulting from
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welcome: Real-time or streaming pipelines Control / robotics / feedback systems Optical systems / optical tweezers / laser-based manipulation Probabilistic modelling / tracking Software in the loop (SiL
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, operation, and optimization of SPS- and PLC-based control systems for experimental equipment and beamline instrumention Integration of hardware and software interfaces (motors, detectors, sensors, sample
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or master’s degree in the field of Law with over-average success Excellent abilities of Austrian Private Law and associated practise areas Excellent command of German (written and spoken) Excellent
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. Specifically, this project leverages industrial communication networks, distributed controllers, AI models, and state-of-the-art IBR-based infrastructure to optimize EV charging and energy systems. By
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; conduct additional modeling, which could include impact models focused on crop water requirements and vegetative health; assist in the development and maintenance of UNIX-based systems for automatic data
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models of the various equipment/tools of an agricultural machine, and virtualisation of their use in the field - Determination of the control logic to be implemented on the platform (proportional valve
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fruitful data to calibrate physics-based crystal plasticity models and inform them with key parameters (e.g., variation of single-crystal elastic constants and critical resolved shear stresses with
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-driven methods provide excellent performance under low or cyclo-stationary regimes but struggle with highly dynamic and rapidly varying conditions; conversely, model-based state observers ensure robustness