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Intelligent Identification of Moisture Control of Drying Process in Paper Machine
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This paper is focuses modeling of the last part of the paper machine – the drying section. Paper is dried by letting it pass through a series of steam heated group of cylinders and the evaporation is thus performed by the latent heat of vaporization of the steam. By adjusting the set point of the steam pressure controllers to the cylinders we can control the moisture in the paper. There exist several incentives to focus on the performance of the moisture control. The time to perform a grade change is often limited by the moisture then time is directly correlated to economic profit. The process model is identified regularly and the changes in its characteristics are observed periodically. This method of identification gives a great advantage over the conventional controller tuning methods, which uses the process model at the nominal operating conditions. A number of structures are available for modeling a process system. Model for the drying process of Paper industry is established based on gathering 1000 groups of 2500 real-time sample data. Based on the collection of data, that was adapted to both the conventional and intelligent modelling process. Finally the suitable model is tuned with the suitable controller for optimal control of the drying process.
Keywords
Drying Process of Paper Machine, System Identification, Artificial Neural Network, T-S Fuzzy Modelling, Hammerstein-Weiner Model.
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