Predicting overhead temperature in distillation column by N-CARARMA model
Year: 2024
Type: article
Abstract: In this paper, a non-linear controlled autoregressive autoregressive moving average (N-CARARMA) model was developed using extended least square algorithm (ELS) and extended stochastic gradient algorithm (ESG) to predict the evolution of the overhead temperature of a distillation column system. The model parameters were estimated and verified by taking input and output data from the separation unit under nominal operating conditions. Three criteria of models selection: Akaike’s Information Criterion (AIC), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency (NSE) are used to estimate the prediction performance of the N-CARARMA model. Using real experimental data, it is showed that the best structure of the proposed model can be used to describe the overhead temperature at different nominal operating conditions.
Authors: Mohamed Zouai, Lakhdar Aggoun, Yahya Chetouani
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405584772