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. Specifically, you will Develop theory and practical algorithms for delay-adaptive model predictive control (MPC) Design delay-adaptive MPC algorithms for safe operation of molten-salt nuclear reactors Co
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Uncertainty-Aware Dynamic Optimisation for Model Predictive Control (in collaboration with Airbus Defence and Space Limited) (C3.5-ELE-Trodden) School of Electrical and Electronic Engineering PhD
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to develop learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor
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and applying optimisation methods, such as model predictive control, multi-objective optimisation and, where appropriate, reinforcement learning Investigating suitable model-reduction and approximation
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as AWS SageMaker Small or large language model development with retrieval-augmented generation Desirable : Industrial analytics or predictive maintenance Knowledge of construction-related industries
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accepted all year round Details Dynamic optimization is integral to many aspects of science and engineering, commonly found in trajectory optimization, optimal control (e.g. model predictive control
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: Determine whether ML provides a genuine advantage over established approaches based on system identification followed by model-based control, including Model Predictive Control and adaptive control
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<span lang="en">Helmholtz-Zentrum Dresden-Rossendorf e. V.</span> | Dresden, Sachsen | Germany | about 9 hours ago
control theory (e.g., model predictive control, fuzzy control, etc.)
- Willingness to work on numerical and experimental tasks
- Excellent teamwork and communication skills in an
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intersection of model predictive control and adaptive modelling and contribute to facilitating the increased penetration of renewable energy through the orchestration of flexible energy consumption. You will
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predictions. • Designing and conducting instrumented WA-DED experiments to validate the developed models. • Applying the CFD-informed FEA model to predict and control temperature fields for building parts with