Iterative Learning Control for Final Batch Product Quality Using Partial Least Squares Models

A terminal iterative learning control (ILC) strategy for batch-to-batch and within-batch control of final product properties, based on empirical partial least squares (PLS) models, is presented. The strategy rejects persistent process disturbances and achieves new final product quality targets using...

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Bibliographic Details
Published in:Industrial & engineering chemistry research 2005-11, Vol.44 (24), p.9146-9155
Main Authors: Flores-Cerrillo, Jesus, MacGregor, John F
Format: Article
Language:English
Subjects:
Applied sciences
Chemical engineering
Exact sciences and technology
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Summary:A terminal iterative learning control (ILC) strategy for batch-to-batch and within-batch control of final product properties, based on empirical partial least squares (PLS) models, is presented. The strategy rejects persistent process disturbances and achieves new final product quality targets using an iterative procedure that works in the reduced space of a latent variable model rather than in the high dimensional space of the manipulated variable trajectories. Complete manipulated variable trajectory reconstruction is then achieved by exploiting the PLS model of the process. The approach is illustrated with a condensation polymerization example for the production of nylon.
ISSN:0888-5885
1520-5045
DOI:10.1021/ie048811p