Subspace identification for data-driven modeling and quality control of batch processes

In this work, we present a novel, data‐driven, quality modeling, and control approach for batch processes. Specifically, we adapt subspace identification methods for use with batch data to identify a state‐space model from available process measurements and input moves. We demonstrate that the resul...

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Vydáno v:AIChE journal Ročník 62; číslo 5; s. 1581 - 1601
Hlavní autoři: Corbett, Brandon, Mhaskar, Prashant
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Blackwell Publishing Ltd 01.05.2016
American Institute of Chemical Engineers
Témata:
Batch processes
Chemical engineering
Computer simulation
control
Mathematical models
Modelling
Polymerization
Polymethyl methacrylates
process control
Quality
Quality control
Subspaces
Terminals
ISSN:0001-1541, 1547-5905
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Shrnutí:In this work, we present a novel, data‐driven, quality modeling, and control approach for batch processes. Specifically, we adapt subspace identification methods for use with batch data to identify a state‐space model from available process measurements and input moves. We demonstrate that the resulting linear time‐invariant (LTI), dynamic, state‐space model is able to describe the transient behavior of finite duration batch processes. Next, we relate the terminal quality to the terminal value of the identified states. Finally, we apply the resulting model in a shrinking‐horizon, model predictive control scheme to directly control terminal product quality. The theoretical properties of the proposed approach are studied and compared to state‐of‐the‐art latent variable control approaches. The efficacy of the proposed approach is demonstrated through a simulation study of a batch polymethyl methacrylate polymerization reactor. Results for both disturbance rejection and set‐point changes (i.e., new quality grades) are demonstrated. © 2016 American Institute of Chemical Engineers AIChE J, 62: 1581–1601, 2016
Bibliografie:ark:/67375/WNG-0CW9CX6X-G
ArticleID:AIC15155
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ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0001-1541
1547-5905
DOI:10.1002/aic.15155