Iterative approaches for closed loop identification for process systems

Closed loop identification of dynamic models is usually performed to get improved control when the dynamic model changes. This project will look at iterative methods to exploit the wealth of information in routine closed loop data to generate high fidelity models for control. The project will develop expertise in model adaptation, closed loop optimization and control. A strong interest in mathematics is desirable and will be developed further.

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