A nested online scheduling and nonlinear model predictive control framework for multi‐product continuous systems

In the pursuit of integrated scheduling and control frameworks for chemical processes, it is important to develop accurate integrated models and computational strategies such that optimal decisions can be made in a dynamic environment. In this study, a recently developed switched system formulation...

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Bibliographic Details
Published in:AIChE journal 2022-05, Vol.68 (5), p.n/a
Main Authors: Andrés‐Martínez, Oswaldo, Ricardez‐Sandoval, Luis A.
Format: Article
Language:English
Subjects:
Chemical reactions
Computer aided scheduling
Computer applications
continuous processes
Decisions
integrated scheduling and control
Model reduction
Nonlinear control
nonlinear model predictive control
online scheduling
Predictive control
Scheduling
switched systems
Switching sequences
System effectiveness
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Summary:In the pursuit of integrated scheduling and control frameworks for chemical processes, it is important to develop accurate integrated models and computational strategies such that optimal decisions can be made in a dynamic environment. In this study, a recently developed switched system formulation that integrates scheduling and control decisions is extended to closed‐loop operation embedded with nonlinear model predictive control (NMPC). The resulting framework is a nested online scheduling and control loop that allows to obtain fast and accurate solutions as no model reduction is needed and no integer variables are involved in the formulations. In the outer loop, the integrated model is solved to calculate an optimal product switching sequence such that the process economics is optimized, whereas in the inner loop, an NMPC implements the scheduling decisions. The proposed scheme was tested on two multi‐product continuous systems. Unexpected large disturbances and rush orders were handled effectively.
ISSN:0001-1541
1547-5905
DOI:10.1002/aic.17665