Çok değişkenli proseste doğrusal olmayan GPC ve kesikli-zaman PID'nin deneysel performansı: Atık yemeklik yağdan biyodizel sentezinde tepkimeli damıtma kolonunun sıcaklık kontrolünde NARIMAX ve ARX modelleri

Year 2022, Volume: 28 Issue: 7, 977 - 986, 30.12.2022

Mehmet Tuncay Çağatay Süleyman Karacan

Abstract

Genelleştirilmiş Öngörülü Kontrol (GPC), çok değişkenli prosesi etkili bir şekilde kontrol edebilme avantajına sahip popüler bir Model Öngörülü Kontrol algoritmasıdır. Bu çalışmada, atık yemeklik yağdan kalsiyum-oksit katalizörlü biyodizel sentezinde tepkimeli damıtma kolonu prosesinin, NARIMAX model tabanlı doğrusal olmayan GPC ve ARX model tabanlı kesikli-zaman PID kontrol ile deneysel sıcaklık denetimi incelenmiştir. Deneyler öncesinde, tüm parametrelerin sıcaklık ve biyodizel mol kesri üzerine etkileri HYSYS simülasyonu ile analiz edilmiştir. Müteakiben, WCO akış hızı ve kazan ısı yükü ayar değişkenleri ve MATLAB'da geliştirilen algoritmalar ve kodlar yardımıyla denetim çalışmaları gerçekleştirilmiştir. SISO deneylerinde, ilgili ayar değişkeni ile kontrol edilen her bir bölgede önemli seviyede yakınsak sıcaklık cevapları elde edilmiştir. MIMO deneyler açısından ise, ayırımsız doğrusal olmayan GPC haricinde, önerilen tüm yöntemlerde en nihayetinde ayar noktalarına yakınsama olduğu tespit edilmiştir, ancak en iyi performans, daha az şiddetli etkileşime sahip, daha küçük yerleşme zamanlı, salınım göstermeyen ve daha düşük IAE ve ISE’ye sahip ayırımlı doğrusal olmayan GPC ile elde edilmiştir.

Keywords

Genelleştirilmiş öngörülü kontrol, PID kontrol, Çok değişkenli kontrol, Tepkimeli damıtma kolonu, Biyodizel, Atık yemeklik yağ

Experimental performances of nonlinear GPC and discrete-time PID in multivariate process: NARIMAX and ARX models in temperature control of reactive distillation column in synthesis of biodiesel from waste cooking oil

Abstract

Generalized Predictive Control (GPC) is a popular Model Predictive Control algorithm that has the advantage of effectively managing the multivariate process. In this study, experimental temperature control of the reactive distillation column process in calcium−oxide catalyzed biodiesel synthesis from waste cooking oil was investigated using nonlinear GPC based on NARIMAX model and discrete time PID control based on ARX model. Before the experiments, the effects of all parameters on temperature and biodiesel mole fraction were analyzed by HYSYS simulation. Afterwards, control studies were carried out with the help of WCO flow rate and reboiler heat duty manipulating variables and algorithms and codes developed in MATLAB. In the SISO experiments, significant convergent temperature responses were obtained in each region controlled by the relevant manipulating variable. Regarding MIMO experiments, all proposed methods except the non-decoupled nonlinear GPC were found to converge ultimately to their setpoints, but the best performance was achieved in decoupled nonlinear GPC with less severe interaction, smaller settling time, no oscillations and lower IAE and ISE.

Keywords

Generalized predictive control, PID control, Multivariable control, Reactive distillation column, Biodiesel, Waste cooking oil

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