An Approach for Feedforward Model Predictive Control of Continuous Pulp Digesters

Rahman Rahman,Kyprianidis Kyprianidis,Avelin Avelin

doi:10.3390/pr7090602

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.

Highlights

Pulp and paper mills convert cellulosic fibers, mostly wood, into pulp and various types of paper products
We focus on the use of near infrared (NIR) spectroscopy-based lignin content measurement coupled to a dynamic process model as an enabler for feedforward model predictive control (FFMPC)
A FFMPC approach for Kappa number control of a continuous pulp digester was investigated in this paper

Summary

Introduction

Pulp and paper mills convert cellulosic fibers, mostly wood, into pulp and various types of paper products. More than half of the globally produced pulp comes from the Kraft or sulfate pulping process. In the Kraft pulping process, the continuous pulp digester is one of the most critical components. The digester is a complex heterogeneous reactor in which white liquor—an aqueous solution of sodium hydroxide and sodium sulfide—reacts with wood chips comprising mainly of cellulose, hemi-cellulose and lignin, to remove lignin and subsequently free wood fibers. We focus on the use of near infrared (NIR) spectroscopy-based lignin content measurement coupled to a dynamic process model as an enabler for feedforward model predictive control (FFMPC). A brief literature review on modeling and predictive control of pulp digesters is presented in the subsequent sections

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