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, MPC), state estimation, system identification and design synthesis problems. A key characteristic of dynamic optimization problems (DOPs) is that the decision variables can be functions or trajectories
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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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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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(secure aggregation, differential privacy, MPC/HE); personalization under heterogeneity; governance-aware data/model sharing; collaborative evaluation. Major Duties and Responsibilities: Conduct
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uncertainty-aware, optimization-based motion planning at the control and planning layer. You will develop scalable trajectory optimization and real-time Model Predictive Control (MPC) strategies that use the
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algorithms for parameter-adaptive model predictive control (MPC) Develop optimal strategies for bidding into multiple markets based on the demand response models Co-supervise MSc and BSc projects on