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Zhang L, Xie J, Dubljevic S. Sensor Location Selection for Continuous Pulp Digesters with Delayed Measurements. AIChE J 2022. [DOI: 10.1002/aic.17862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Lu Zhang
- Department of Chemical & Materials Engineering University of Alberta Edmonton AB Canada
| | - Junyao Xie
- Department of Chemical & Materials Engineering University of Alberta Edmonton AB Canada
| | - Stevan Dubljevic
- Department of Chemical & Materials Engineering University of Alberta Edmonton AB Canada
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Zhang L, Xie J, Dubljevic S. Dynamic modeling and model predictive control of a continuous pulp digester. AIChE J 2021. [DOI: 10.1002/aic.17534] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Lu Zhang
- Department of Chemical & Materials Engineering University of Alberta Edmonton Alberta Canada
| | - Junyao Xie
- Department of Chemical & Materials Engineering University of Alberta Edmonton Alberta Canada
| | - Stevan Dubljevic
- Department of Chemical & Materials Engineering University of Alberta Edmonton Alberta Canada
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A Review on the Modeling, Control and Diagnostics of Continuous Pulp Digesters. Processes (Basel) 2020. [DOI: 10.3390/pr8101231] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Being at the heart of modern pulp mills, continuous pulp digesters have attracted much attention from the research community. In this article, a comprehensive review in the area of modeling, control and diagnostics of continuous pulp digesters is conducted. The evolution of research focus within these areas is followed and discussed. Particular effort has been devoted to identifying the state-of-the-art and the research gap in a summarized way. Finally, the current and future research directions in the areas have been analyzed and discussed. To date, digester modeling following the Purdue approach, Kappa number control using model predictive controllers and health index-based diagnostic approaches by utilizing different statistical methods have dominated the field. While the rising research interest within the field is evident, we anticipate further developments in advanced sensors and integration of these sensors for improving model prediction and controller performance; and the exploration of different AI-based approaches will be at the core of future research.
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An Approach for Feedforward Model Predictive Control of Continuous Pulp Digesters. Processes (Basel) 2019. [DOI: 10.3390/pr7090602] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Kappa number variability at the continuous digester outlet is a major concern for pulp and paper mills. It is evident that the aforementioned variability is strongly linked to the feedstock wood properties, particularly lignin content. Online measurement of lignin content utilizing near-infrared spectroscopy at the inlet of the digester is paving the way for tighter control of the blow-line Kappa number. In this paper, an innovative approach of feedforwarding the lignin content to a model predictive controller was investigated with the help of modeling and simulation studies. For this purpose, a physics-based modeling library for continuous pulp digesters was developed and validated. Finally, model predictive control approaches with and without feedforwarding the lignin measurement were evaluated against current industrial control and proportional-integral-derivative (PID) schemes.
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Affiliation(s)
- Thomas McAvoy
- Department of Chemical Engineering, Institute for Systems Research, University of Maryland, College Park, Maryland 20742
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