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Field
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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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information extraction. Advanced algorithms will be developed to obtain useful information such as the 3D flame topology and spread velocity. The candidate should have a good background in mathematics and they
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practices produced with the help of computer algorithms challenge, subvert and threaten the modernist concept of the author. AI generated creative practices have the capacity to seriously disrupt established
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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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optimise the algorithms for optimal process control. The research will benefit from the available experimental facilities including laboratory-scale digesters, excellent analytical facilities, expertise in