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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Bibliographic Details
Published inIndustrial & engineering chemistry research Vol. 52; no. 35; pp. 12437 - 12450
Main Authors Yu, Honglu, Flores-Cerrillo, Jesus
Format Journal Article
LanguageEnglish
Published American Chemical Society 04.09.2013
Subjects
Algorithms
Design engineering
Exothermic reactions
Mathematical models
Methodology
Predictive control
Robustness
Tracking
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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