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Two case studies for applying Model Predictive Controllers on chemical processes

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Two case studies for applying Model Predictive Controllers on chemical processes. / Pour, N. Danesh; Montazeri, A.; Poshtan, J. et al.
Industrial Electronics Society, 2007. IECON 2007. 33rd Annual Conference of the IEEE. New York: IEEE, 2007. p. 580-585 (IEEE Industrial Electronics Society).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Pour, ND, Montazeri, A, Poshtan, J & Motlahgh, MRJ 2007, Two case studies for applying Model Predictive Controllers on chemical processes. in Industrial Electronics Society, 2007. IECON 2007. 33rd Annual Conference of the IEEE. IEEE Industrial Electronics Society, IEEE, New York, pp. 580-585, 33rd Annual Conference of the IEEE-Industrial-Electronics-Society, Taipei, 5/11/07. https://doi.org/10.1109/IECON.2007.4460024

APA

Pour, N. D., Montazeri, A., Poshtan, J., & Motlahgh, M. R. J. (2007). Two case studies for applying Model Predictive Controllers on chemical processes. In Industrial Electronics Society, 2007. IECON 2007. 33rd Annual Conference of the IEEE (pp. 580-585). (IEEE Industrial Electronics Society). IEEE. https://doi.org/10.1109/IECON.2007.4460024

Vancouver

Pour ND, Montazeri A, Poshtan J, Motlahgh MRJ. Two case studies for applying Model Predictive Controllers on chemical processes. In Industrial Electronics Society, 2007. IECON 2007. 33rd Annual Conference of the IEEE. New York: IEEE. 2007. p. 580-585. (IEEE Industrial Electronics Society). doi: 10.1109/IECON.2007.4460024

Author

Pour, N. Danesh ; Montazeri, A. ; Poshtan, J. et al. / Two case studies for applying Model Predictive Controllers on chemical processes. Industrial Electronics Society, 2007. IECON 2007. 33rd Annual Conference of the IEEE. New York : IEEE, 2007. pp. 580-585 (IEEE Industrial Electronics Society).

Bibtex

@inproceedings{6a9f014a79cf4db782bebec13e00b880,
title = "Two case studies for applying Model Predictive Controllers on chemical processes",
abstract = "Implementation of Model Predictive Control as the most famous advanced process control method, in real processes has some practical issues that are ignored in many simulation studies and needs more attention especially in implementing the controller. For this purpose, in this paper two chemical processes are simulated in HYSYS software as a more realistic environment that exhibits many properties of real plants. The control and identification is performed by connecting HYSYS and MATLAB softwares in a real-time manner. Some of the train practical issues that are considered here are: pre-test of the plant, test design and identification requirements, dealing with low-level control loops and controller tuning to attain the best performance. Simulation results show that without having enough knowledge on such important points, practical implementation of this very useful advanced process control method will be very challenging.",
author = "Pour, {N. Danesh} and A. Montazeri and J. Poshtan and Motlahgh, {M. R. Jahed}",
year = "2007",
doi = "10.1109/IECON.2007.4460024",
language = "English",
isbn = "978-1-4244-0783-5",
series = "IEEE Industrial Electronics Society",
publisher = "IEEE",
pages = "580--585",
booktitle = "Industrial Electronics Society, 2007. IECON 2007. 33rd Annual Conference of the IEEE",
note = "33rd Annual Conference of the IEEE-Industrial-Electronics-Society ; Conference date: 05-11-2007 Through 08-11-2007",

}

RIS

TY - GEN

T1 - Two case studies for applying Model Predictive Controllers on chemical processes

AU - Pour, N. Danesh

AU - Montazeri, A.

AU - Poshtan, J.

AU - Motlahgh, M. R. Jahed

PY - 2007

Y1 - 2007

N2 - Implementation of Model Predictive Control as the most famous advanced process control method, in real processes has some practical issues that are ignored in many simulation studies and needs more attention especially in implementing the controller. For this purpose, in this paper two chemical processes are simulated in HYSYS software as a more realistic environment that exhibits many properties of real plants. The control and identification is performed by connecting HYSYS and MATLAB softwares in a real-time manner. Some of the train practical issues that are considered here are: pre-test of the plant, test design and identification requirements, dealing with low-level control loops and controller tuning to attain the best performance. Simulation results show that without having enough knowledge on such important points, practical implementation of this very useful advanced process control method will be very challenging.

AB - Implementation of Model Predictive Control as the most famous advanced process control method, in real processes has some practical issues that are ignored in many simulation studies and needs more attention especially in implementing the controller. For this purpose, in this paper two chemical processes are simulated in HYSYS software as a more realistic environment that exhibits many properties of real plants. The control and identification is performed by connecting HYSYS and MATLAB softwares in a real-time manner. Some of the train practical issues that are considered here are: pre-test of the plant, test design and identification requirements, dealing with low-level control loops and controller tuning to attain the best performance. Simulation results show that without having enough knowledge on such important points, practical implementation of this very useful advanced process control method will be very challenging.

U2 - 10.1109/IECON.2007.4460024

DO - 10.1109/IECON.2007.4460024

M3 - Conference contribution/Paper

SN - 978-1-4244-0783-5

T3 - IEEE Industrial Electronics Society

SP - 580

EP - 585

BT - Industrial Electronics Society, 2007. IECON 2007. 33rd Annual Conference of the IEEE

PB - IEEE

CY - New York

T2 - 33rd Annual Conference of the IEEE-Industrial-Electronics-Society

Y2 - 5 November 2007 through 8 November 2007

ER -