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, including how to guarantee the properties of stability and constraint satisfaction while probing the system and learning a new model. This project aims to develop novel algorithms for the adaptive distributed
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/adaptive algorithms, offline and online data analysis, conducting experimental research, and online evaluation of the developed adaptive strategies with a robotic application. The prospective students can
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project may also contain an application side where you can test your algorithms on power systems and energy markets. This is a 3.5 year scholarship. This funding opportunity is open to both home and
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Optimization-based control explores the use of optimization algorithms for feedback control of dynamical systems. For example, model predictive control (MPC) is a widely used optimization-based control method
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algorithms that would allow the delay and/or suppression of hysteresis effects in dynamic stall through the use of control surfaces, for example, allowing the safe recovery of aircraft from post-stall
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adapted based on the abilities and needs of patients. Moreover, automatic intelligent algorithms will be developed in to make the control intuitive, natural and adaptive. Such that the model can learn new
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using their high performance computational mechanics algorithm Alya, by coupling solid mechanics with electrophysiology. This project aims to personalise this model using medical images (MRI) collected
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between the brain signals of different subjects. The aim of this project is developing new adaptive and machine learning algorithms to successfully decode brain signals across subjects. The prospective
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. The ultimate goal is to develop theory and methods for the construction of low-complexity invariant sets, using computationally tractable algorithms. Funding Notes This is a self-funded research project. We
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finite element modelling to simulate the deformation of microstructures, novel crack propagation simulation techniques and scale-transition algorithms. The model will be informed and validated using full