A Hybrid Model Based Model Predictive Control Strategy for Particle Processes

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Abstract

Control of particle processes is a challenging task due to their complex and multivariable kinetics. The outcome of these processes, including crystallization, flocculation and emulsification, must comply with a given set of quality attributes related to particle properties. In an industrial setting, failure to comply with these quality attributes typically results in either reprocessing or even disposal of the product. Advanced control strategies, such as model predictive control is one way to tackle these issues optimally. However, they require the development of predictive process model whose cost may be out of proportion to the price of the product. It is therefore likely that more advanced control strategies are to be actively deselected in the development of new processes.
Original languageEnglish
Publication date2020
Publication statusPublished - 2020
Event2020 AIChE Annual Meeting - Virtual event
Duration: 16 Nov 202020 Nov 2020

Conference

Conference2020 AIChE Annual Meeting
LocationVirtual event
Period16/11/202020/11/2020

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