In this study, an Autoregressive with eXogenous input (ARX) model and an Autoregressive Moving Average with eXogenous input (ARMAX) model are developed to predict the overhead temperature of a distillation column. The model parameters are estimated using the recursive algorithms. In order to select an optimal model for the process, different performance measures, such as Aikeke's Information Criterion (AIC), Root Mean Square Error (RMSE), and Nash–Sutcliffe Efficiency (NSE), are calculated.
Recursive Identification of the Dynamic Behavior in a Distillation Column by Means of Autoregressive Models
Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received August 9, 2013; final manuscript received February 5, 2014; published online April 28, 2014. Assoc. Editor: Ryozo Nagamune.
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Aggoune, L., Chetouani, Y., and Radjeai, H. (April 28, 2014). "Recursive Identification of the Dynamic Behavior in a Distillation Column by Means of Autoregressive Models." ASME. J. Dyn. Sys., Meas., Control. July 2014; 136(4): 044506. https://doi.org/10.1115/1.4026837
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