0
Technical Brief

Recursive Identification of the Dynamic Behavior in a Distillation Column by Means of Autoregressive Models

[+] Author and Article Information
Lakhdar Aggoune

Laboratoire d'Automatique de Sétif,
Département d'Electrotechnique,
Université de Sétif 1,
Cité Maabouda, Route de Béjaia,
Sétif 19000, Algeria
e-mail: lakhdar.aggoune@yahoo.fr

Yahya Chetouani

Département Génie Chimique,
Université de Rouen,
Rue Lavoisier,
Mont Saint Aignan Cedex 76821, France
e-mail: yahya.chetouani@univ-rouen.fr

Hammoud Radjeai

Laboratoire d'Automatique de Sétif,
Département d'Electrotechnique,
Université de Sétif 1,
Cité Maabouda, Route de Béjaia,
Sétif 19000, Algeria
e-mail: hradjeai@yahoo.fr

1Corresponding author.

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.

J. Dyn. Sys., Meas., Control 136(4), 044506 (Apr 28, 2014) (5 pages) Paper No: DS-13-1313; doi: 10.1115/1.4026837 History: Received August 09, 2013; Revised February 05, 2014

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.

FIGURES IN THIS ARTICLE
<>
Copyright © 2014 by ASME
Your Session has timed out. Please sign back in to continue.

References

Ljung, L., 1999, System Identification, Theory for the User, Prentice-Hall, Englewood Cliffs, NJ.
Landau, I. D., Lozano, R., M'Saad, M., and Karimi, A., 2011, Adaptive Control: Algorithms, Analysis and Applications, Springer-Verlag, London.
Muddu, M., Naraga, A., and Patwardhan, S. C., 2010, “Reparametrized ARX Models for Predictive Control of Staged and Packed Bed Distillation Columns,” Control Eng. Pract., 18, pp. 114–130. [CrossRef]
Chetouani, Y., 2011, “Detecting Changes in Distillation Column by Using a Sequential Probability Ratio Test,” Syst. Eng. Procedia, 1, pp. 473–480. [CrossRef]
Qin, S. J., and Badgwell, T. A., 2004, “A Survey of Industrial Model Predictive Control Technology,” Control Eng. Pract., 11, pp. 733–767. [CrossRef]
Chetouani, Y., 2009, “Model-Order Reduction Based on Artificial Neural Networks for Accurate Prediction of the Product Quality in a Distillation Column,” Int. J. Autom. Control, 3, pp. 332–351. [CrossRef]
Bouamama, B. O., Staroswiecki, M., Dauphin-Tanguy, G., Khellassi, A., Zelmat, M., and Benhalla, A., 2001, “Monitoring Ability Analysis Using Bond Graph Approach: Application to Distillation Column,” Proceeding of 4th IFAC Workshop on ‘‘On-line Fault Detection and Supervision in the Chemical Process Industries, Jejudo, South Korea, June 7–8, pp. 388–393.
Huyck, B., De Brabanter, K., Logist, F., Van Impe, J., and De Moor, B., 2011, " Identification of a Pilot Scale Distillation Column: A Kernel Based Approach,” Proceeding of 18th IFAC Congress, Milano, Italy, Aug. 28–Sep. 2, pp. 471–476.
Nugroho, S., Nazaruddin, Y. Y., and Tjokronegoro, H. A., 2004, “Non-linear Identification of Aqueous Ammonia Binary Distillation Column Based on Simple Hammerstein Model,” Proceeding of 5th Asian Control Conference, Melbourne, Australia, July 20–23, pp. 118–123.
Zhu, Y., 1999, “Distillation Column Identification for Control Using Wiener Model,” Proceeding of American Control Conference, San Diego, CA. June 2–4, pp. 3462–3466.
Ríos-Moreno, G. J., Trejo-Perea, M., Castañeda-Miranda, R., Hernández-Guzmán, V. M., and Herrera-Ruiz, G., 2007, “Modelling Temperature in Intelligent Buildings by Means of Autoregressive Models,” Autom. Constr.16, pp. 713–722. [CrossRef]
Hervé, A., Sipp, D., Schmid, P. J., and Samuelides, M., 2012, “A Physics-Based Approach to Flow Control Using System Identification,” J. Fluid Mech., 702, pp. 26–58. [CrossRef]
Akaike, H., 1974, " A New Look at the Statistical Model Identification,” IEEE Trans. Autom. Control, 19, pp. 716–723. [CrossRef]
Nash, J. E., and Sutcliffe, J. V., 1970, “River Flow Forecasting Through Conceptual Models,” J. Hydrol., 10, pp. 282–290. [CrossRef]
Billings, S. A., and Voon, W. S. F., 1986, “Correlation Based Model Validity Tests for Non-linear Models,” Int. J. Control, 44, pp. 235–244. [CrossRef]

Figures

Grahic Jump Location
Fig. 5

Comparison between measured and predicted overhead temperature using ARMAX model

Grahic Jump Location
Fig. 6

The prediction error for the ARMAX model

Grahic Jump Location
Fig. 1

Experimental device: Distillation column

Grahic Jump Location
Fig. 2

Inputs and output of the column model

Grahic Jump Location
Fig. 3

Estimation and validation data

Grahic Jump Location
Fig. 4

Evolution of pressure drop (ΔP), reflux timer (Rt), heating power (Qf), and preheating power (Qb)

Grahic Jump Location
Fig. 7

Correlation test results

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In