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Latent Variable Model Predictive Control for Trajectory Tracking in Batch Processes: Internal Model Control Interpretation and Design Methodology
In this paper, a theoretical analysis of the latent variable model predictive control (LV-MPC) algorithm, originally proposed by Flores-Cerrillo and MacGregor, is presented. The properties of the algorithm in terms of stability, robustness, and control performance are analyzed. An off-line design me...
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Published in: | Industrial & engineering chemistry research 2013-09, Vol.52 (35), p.12437-12450 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | In this paper, a theoretical analysis of the latent variable model predictive control (LV-MPC) algorithm, originally proposed by Flores-Cerrillo and MacGregor, is presented. The properties of the algorithm in terms of stability, robustness, and control performance are analyzed. An off-line design methodology, using Internal Model Control framework (IMC), to determine the adequate range of the LV-MPC parameters is proposed. The excellent control performance and robustness of the off-line design methodology is illustrated for the temperature tracking of an emulsion polymerization process and an exothermic chemical reaction system. |
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ISSN: | 0888-5885 1520-5045 |
DOI: | 10.1021/ie400060j |