We propose a novel integrated methodology for taking into account model uncertainty, in the form of uncertain parameters, within a previously published real time dynamic optimization and optimal control strategy. The combined approach, designed for batch processes, is scenario-based and consists of two interacting layers: one, which computes the optimal operating conditions and takes control actions in response to disturbances, and the other, which executes the dynamic scenario updating strategy. The approach is applied to a fed-batch reactor to demonstrate its effectiveness and flexibility.

Dynamic Multi-Scenario Approach to Robust and Profitable Online Optimization & Optimal Control of Batch Processes

MANENTI, FLAVIO
2016

Abstract

We propose a novel integrated methodology for taking into account model uncertainty, in the form of uncertain parameters, within a previously published real time dynamic optimization and optimal control strategy. The combined approach, designed for batch processes, is scenario-based and consists of two interacting layers: one, which computes the optimal operating conditions and takes control actions in response to disturbances, and the other, which executes the dynamic scenario updating strategy. The approach is applied to a fed-batch reactor to demonstrate its effectiveness and flexibility.
Computer Aided Chemical Engineering
9780444634283
9780444634283
dynamic and optimal scenario mapping; robust online optimization; robust optimal control; Chemical Engineering (all); Computer Science Applications1707 Computer Vision and Pattern Recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1003028
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