Kesikli Bir Polimerizasyon Reaktörüne Farklı Optimal Şartlarda Sıcaklık Kontrolunun Uygulanması

Genelleştirilmiş öngörmeli kontrol(GPC) ile genelleştirilmiş delta kuralı(GDK) izotermal koşullar altında stirenin polimerizasyonunun gerçekleştiği ceketli kesikli bir reaktörün sıcaklığını kontrol etmede kullanılmıştır. Monomer dönüşümü, viskozite ortalama molekül ağırlığı ve zincir uzunluğu üzerine değişik optimal koşulların etkileri incelenmiştir. Reaktör sıcaklığı ve reaktöre verilen ısı arasındaki etkileşime dayanan yapay sinir ağı modeli kullanılmıştır. GPC’li GDK’nın etkinliği belirlenen sabit sıcaklıklarda GDK parametreleri kullanılarak deneysel ve benzetim ile incelenmiştir. Sonuçlar Self-Tuning PID (STPID) yöntemi ile karsılaştırılmıştır. Kontrol deneyleri sonucunda GDK-GPC kontrol yönteminin iyi bir performans gösterdiği ve istenilen özelliklerde polimer elde edildiği gözlenmiştir. Ayrıca GDK-GPC yönteminin STPID yönteminden daha iyi olduğu hem kontrol performansından hem de elde edilen polimer özelliklerinden gözlenmektedir.

APPLICATION OF TEMPERATURE CONTROL IN A BATCH POLYMERIZATION REACTOR AT DIFFERENT OPTIMAL TEMPERATURES

The generalized delta rule (GDR) algorithm with generalized predictive control (GPC) was used to control the temperature of a jacketed batch reactor in which styrene polymerization occurs under isothermal conditions. The effects of different optimal conditions were examined on monomer conversion, average viscosity molecular weight and chain length. The neural network model based on the relation between the reactor temperature and heat input to the reactor was used. The efficiency of the GDR with GPC was examined by simulation and experimentally using GDR parameters specified at constant temperatures, and compared with Self-Tuning PID (STPID). It was observed that the control experiments provided a good performance in maintaining the reactor temperature at its set point and yielded polymer product with desired properties. 

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