CPAG (2024), (стр. 111-118)
АУТОР(И) / AUTHOR(S): Domagoj Bratek, Mihael Cikoja
DOI: 10.46793/CPAG24.111B
САЖЕТАК / ABSTRACT:
The paper describes adaptive model predictive control applications in paper industry. Paper production as complex system that consists of many mechanical, chemical, thermal and electrical subsystems is a perfect candidate for applying adaptive model predictive control. Main reason for that is successive nature of the process and its high speed. Due to those two facts, procedure of stopping and restarting of the machine is usually a critical process.
At the beginning, paper describes paper production, model predictive control (MPC) and adaptive model predictive control as its improvement.
Furthermore, paper describes application of adaptive MPC in automatic grade change (AGC) in paper production. Differences between standard AGC and advanced AGC are mentioned. Some results obtained during testing in Paper Mill Belisce are presented.
In the addition article describes how mathematical model from adaptive MPC can be applied to soft or virtual sensors. Two examples are mentioned, virtual basis weight and moisture sensor and mechanical properties sensor. Possible applications of these sensor are presented, like improvement of paper properties after sheetbreak or increasing of paper quality etc.
At the end, paper deals with application of adaptive MPC in paper machine wet end optimization. Possible improvements in chemical dosages, sheet break reductions have been presented
КЉУЧНЕ РЕЧИ / KEYWORDS:
Adaptive Model Predictive Control, Advanced Automatic Grade Change, Soft Sensors, Wet-End Optimization
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