Data-Driven Optimal Control for Pulp Washing Process Based on Neural Network
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-22
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Pulp washing process has the features of multivariate, time delay, nonlinearity.
Considering the difficulties of modeling and optimal control in pulp washing process, a data-driven operational-pattern optimization method is proposed to model and optimize the pulp washing process in this paper.
The most important quality indexes of pulp washing performance are residual soda in the washed pulp and Baume degree of extracted black liquor.
Considering the difficulties of modeling, online measurement of these indexes, two-step neural networks, and multivariate logistic regression are used to establish the prediction models of residual soda and Baume degree.
The mathematical model of the washing process can be identified, and the indexes can meet the production requirements.
In the target of better product quality, low cost, and low energy consumption, a multiobjective problems is solved by ant colony optimization algorithm based on the optimized operational-pattern database.
It shows that the theoretical analyses are correct and the practical applications are feasible, optimization control system has been designed for the pulp washing process, and the practical results show that pulp production increased by 20% and water consumption decreased by nearly 30%.
This method is effective in the pulp washing process.
American Psychological Association (APA)
Shan, Wenjuan& Tang, Wei. 2020. Data-Driven Optimal Control for Pulp Washing Process Based on Neural Network. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1202495
Modern Language Association (MLA)
Shan, Wenjuan& Tang, Wei. Data-Driven Optimal Control for Pulp Washing Process Based on Neural Network. Mathematical Problems in Engineering No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1202495
American Medical Association (AMA)
Shan, Wenjuan& Tang, Wei. Data-Driven Optimal Control for Pulp Washing Process Based on Neural Network. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1202495
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202495