Control scheme selection and optimal tuning in industrial process control using factorial experiment design

Authors

DOI:

https://doi.org/10.17533/udea.redin.20201010

Keywords:

optimal control tuning, process control, design of experiments, factorial design

Abstract

In this study, a novel experimental approach for the optimal selection of an actuator-based control strategy is presented. The proposed approach is a two-stage method: first, a two-level factorial experiment design with n factors (2n) was applied to compare different control schemes. Schemes comparison was carried out in terms of energy consumption and closed-loop performance. For the best relative scheme, a Central Composite Face-centered (CCF) design was completed obtaining the controller parameters that optimize the performance in terms of the Integral Absolute Error (IAE) while operating in a region of low energy consumption. The proposed approach was experimentally tested using real data obtained from a laboratory prototype plant. Some experimental tests illustrating the suitability of our method are shown at the end of this article.

|Abstract
= 1009 veces | HTML
= 0 veces| | PDF
= 501 veces|

Downloads

Download data is not yet available.

Author Biographies

David Roberto Acosta Villamil, University of the North

PhD Student, Mechanical Engineering Department.

José Fernando Noguera Polania, Cooperative University of Colombia

PhD, Full-Time Professor, Electronic Engineering Program.

Arnaldo Verdeza Villalobos, Simón Bolívar University

PhD Student, Mechanical Engineering Department.

Blanca Luz Foliaco Romero, University of the North

Doctoral Student, Department of Mechanical Engineering.

 

 

 

 

 

Adriana Fernanda Rincón Montenegro, University of the North

PhD Student, Mechanical Engineering Department.

Marco Enrique Sanjuan Mejía, University of the North

Professor, Mechanical Engineering Department.

References

C. Knospe, “PID control,” IEEE Control Syst. Mag., vol. 26, no. 1, February 2006. [Online]. Available: https://doi.org/10.1109/MCS.2006.1580151

M. L. Brisk, “Process control: Potential benefits and wasted opportunities,” Aust. J. Electr. Electron. Eng., vol. 2, no. 1, 2005. [Online]. Available: https://doi.org/10.1080/1448837X.2005.11464113

P. Klán and R. Gorez, “PI controller design for actuator preservation,” IFAC Proc. Vol., vol. 41, no. 2, 2008. [Online]. Available: https://doi.org/10.3182/20080706-5-KR-1001.00981

F. Castrillón and D. Castellanos, “New tuning rules for PID controllers based on IMC with minimum IAE for inverse response processes,” DYNA, vol. 82, no. 194, November 2015. [Online]. Available: http://dx.doi.org/10.15446/dyna.v82n194.46744

A. Verdeza and L. Di Mare and M. Sanjuán and A. Bula, “Diseño de ecuaciones de sintonía para controladores PID (Proporcional-Integral-Derivativo) implementados en fotobiorreactores,” Inf. tecnológica, vol. 27, no. 4, 2016. [Online]. Available: http://dx.doi.org/10.4067/S0718-07642016000400013

J. Duarte and W. Orozco, “Optimización de sintonización de controladores PID bajo el criterio IAE aplicados a procesos térmicos,” Revista Inge@UAN, vol. 5, no. 10, pp. 35–45, 2015.

J. Shen, “New tuning method for PID controller,” ISA Trans., vol. 41, no. 4, October 2002. [Online]. Available: https://doi.org/10.1016/S0019-0578(07)60103-7

M. T. Özdemir and D. Öztürk and Ī. Eke and V. Çelik and K. Y. Lee, “Tuning of optimal classical and fractional order PID parameters for automatic generation control based on the bacterial swarm optimization,” IFAC-PapersOnLine, vol. 48, no. 30, 2015. [Online]. Available: https://doi.org/10.1016/j.ifacol.2015.12.429

O. García, D. Acosta, and C. Diaz, “GPU-Implementation of a sequential monte carlo technique for the localization of an ackerman robot,” in International Conference on Applied Informatics ICAI 2018: Applied Informatics, Bogotá, Colombia, 2018, pp. 309–320.

J. A. López, A. Duque, and A. F. Navas, “Sintonización de un controlador PID en un PLC haciendo uso de inteligencia de enjambres/auto-tuning of a PID controller implemented in a PLC using swarm intelligence,” Prospectiva, vol. 15, no. 1, January 2017. [Online]. Available: https://doi.org/10.15665/rp.v15i1.679

M. Bauer, A. Horch, L. Xie, M. Jelali, and N. Thornhill, “The current state of control loop performance monitoring – A survey of application in industry,” J. Process Control, vol. 38, February 2016. [Online]. Available: https://doi.org/10.1016/j.jprocont.2015.11.002

K. L. Morales and H. D. Álvarez, “Determination and use of feasible operation region in flash distillation control,” Revista Facultad de Ingeniería Universidad de Antioquia, vol. 95, April 2020. [Online]. Available: http://dx.doi.org/10.17533/udea.redin.20190738

A. S. Comas, A. T. Palacio, S. T. Mendoza, and D. N. Rodado, “Aplicación del diseño de experimentos taguchi para la identificación de factores de influencias en tiempos de impresión 3d con modelado por deposición fundida,” Int. J. Manag. Sci. Oper. Res., vol. 1, no. 1, pp. 43–48, Jan. 2016.

D. C. Montgomery, Design and analysis of experiments, 9th ed. John wiley & sons, 2017.

J. C. Salazar and A. B. Zapata, “Análisis y diseño de experimentos aplicados a estudios de simulación,” DYNA, vol. 76, no. 159, pp. 249– 257, Sep. 2009.

K. J. Åström and T. Hägglund, Advanced PID control. ISA-The Instrumentation, Systems, and Automation Society, 2006.

C. A. Smith and A. B. Corripio, Principles and Practice of Automatic Process Control, 3rd ed. John wiley & sons, 2006.

J. Duarte and et al, “Auto-ignition control in spark-ignition engines using internal model control structure,” J. Energy Resour. Technol., vol. 139, no. 2, March 2017. [Online]. Available: https://doi.org/10. 1115/1.4034026

H. Zeng and K. Xiao, “A new design of multivariable decoupling internal model controller,” J. Theor. Appl. Inf. Technol., vol. 48, no. 1, pp. 417–422, Feb. 2013.

Downloads

Published

— Updated on 2020-10-29

How to Cite

Acosta Villamil, D. R., Noguera Polania, J. F., Verdeza Villalobos, A., Foliaco Romero, B. L., Rincón Montenegro, A. F., & Sanjuan Mejía, M. E. (2020). Control scheme selection and optimal tuning in industrial process control using factorial experiment design. Revista Facultad De Ingeniería Universidad De Antioquia, (103), 34–43. https://doi.org/10.17533/udea.redin.20201010