Volume 67, Issue 9 e17301
PROCESS SYSTEMS ENGINEERING

Application of offset-free Koopman-based model predictive control to a batch pulp digester

Sang Hwan Son

Sang Hwan Son

Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas, USA

Contribution: Conceptualization, Data curation, Formal analysis, ​Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review & editing

Search for more papers by this author
Hyun-Kyu Choi

Hyun-Kyu Choi

Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas, USA

Contribution: Conceptualization, Data curation, ​Investigation, Validation, Writing - review & editing

Search for more papers by this author
Joseph Sang-Il Kwon

Corresponding Author

Joseph Sang-Il Kwon

Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas, USA

Correspondence

Joseph Sang-Il Kwon, Artie McFerrin Department of Chemical Engineering, Texas A&M University, College station, TX 77840.

Email: [email protected]

Contribution: Conceptualization, Formal analysis, Funding acquisition, Resources, Supervision, Writing - review & editing

Search for more papers by this author
First published: 07 May 2021
Citations: 18

Funding information: Artie McFerrin Department of Chemical Engineering and the Energy Institute, Texas A and M University

Abstract

This work presents the application of a Koopman operator approach to a batch pulp digester. To manufacture paper products with desired properties, it is essential to consider both macroscopic and microscopic attributes of pulp. However, the complexity of multiscale dynamics of pulping processes hinders proper control system design. Therefore, we utilize extended dynamic mode decomposition (EDMD), which is based on Koopman operator theory, to derive a global linear representation of a pulp digester. Then, we design an offset-free Koopman-based model predictive control (KMPC) system to regulate the Kappa number and cell wall thickness (CWT) of fibers at a batch pulp digester while compensating for the influence of plant-model mismatch and disturbance during operation. The numerical experiments demonstrate that the linear state-space model, obtained via EDMD, properly predicts the behavior of a batch pulp digester, and the designed offset-free KMPC system successfully drives the Kappa number and CWT to set-point values.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.