Model-order selection of outpur-error models-BSM1 as case study

Authors: Christian Wallin, Jesús Zambrano

Conference: SIMS 2018 

Abstract: Kappa number, which essentially indicates the amount of lignin left in the pulp after cooking, is the most important physical quantity linked to the quality and economics of a Kraft-pulp mill. Controlling the Kappa number is a difficult task mainly due to the naturally varying feedstock, significant residence time, insufficient measurements and complex nature of the delignification process. Moreover, faults such as screen clogging, hang-ups and channeling in the process often occur and increase the operational costs considerably. In this work, the possibility of feedforwarding the lignin content of incoming wood chips, by a near-infrared spectroscopic measurement of one of the major process disturbances, to a model predictive controller, is investigated by means of modeling and simulation studies. Additionally, a simple Bayesian network based diagnostics approach is proposed to detect the continuous digester faults.

Key words: Benchmark Simulation Model No.1, Model Predictive Control, Output Error Model, System Identification.

Download the paper here: sims-2018-mimo-final-updated