Multiscale modeling and multiobjective control of wood fiber morphology in batch pulp digester

Choi, Hyun‐Kyu; Kwon, Joseph

doi:10.1002/aic.16972

Cited by 43 publications

(11 citation statements)

References 39 publications

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“…where T c , A n , R and E n are the chip temperature, pre-exponential factors, universal gas constant and activation energies of the reaction, respectively. In a more recent work, Choi and Kwon [35] extended the Purdue model to capture the evolutions of cell wall thickness and fiber length for batch digesters by integrating the macroscopic model with a microscopic model.…”

Section: Purdue Modelmentioning

confidence: 99%

A Review on the Modeling, Control and Diagnostics of Continuous Pulp Digesters

2020

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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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Section: Purdue Modelmentioning

confidence: 99%

A Review on the Modeling, Control and Diagnostics of Continuous Pulp Digesters

2020

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“…Based on this multiscale modeling framework, Choi and Kwon 26 developed a multiscale model that tracks the CWT value of fibers and considers the fiber collapse phenomenon. Then, Choi and Kwon 27 further improved the multiscale model to capture the fiber breakage phenomenon during pulping. Most recently, Son et al 28 developed a multiscale model that runs multiple kMC simulations in parallel to incorporate the influence of fiber‐to‐fiber heterogeneity on macroscopic phenomena (e.g., diffusion and heat transfer).…”

Section: Introductionmentioning

confidence: 99%

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

2021

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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.

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“…Alexandridis and Sarimveis 19 employed an adaptive MPC based on a radial basis function ANN model for Kappa number control of continuous pulp digesters. Choi and Kwon 20–23 developed a class of MPC for a continuous pulp digester and a batch pulp digester based on the proposed multi‐scale model. However, even though the aforementioned works have made a valuable contribution toward the modeling and controller design for the pulp digester, there still some aspects that did not receive much attention and/or accurate consideration.…”

Section: Introductionmentioning

confidence: 99%

Dynamic modeling and model predictive control of a continuous pulp digester

2021

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This work explores the design of a model predictive controller of the continuous pulp digester process consisting of the co-current zone and counter-current zone modeled by a set of nonlinear coupled hyperbolic partial differential equations (PDEs). The distributed parameter system of interest is not spectral, and slow-fast dynamic separation does not hold. To address this challenge, the nonlinear continuous-time model is linearized and discretized in time utilizing the Cayley-Tustin discretization framework, which ensures system theoretic properties and structure preservation without spatial discretization or model reduction. The discrete model is used in the full state model predictive controller design, which is augmented by the Luenberger observer design to achieve the output constrained regulation. Finally, a numerical example is provided to demonstrate the feasibility and applicability of the proposed controller designs.

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Multiscale modeling and multiobjective control of wood fiber morphology in batch pulp digester

Cited by 43 publications

References 39 publications

A Review on the Modeling, Control and Diagnostics of Continuous Pulp Digesters

A Review on the Modeling, Control and Diagnostics of Continuous Pulp Digesters

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

Dynamic modeling and model predictive control of a continuous pulp digester

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