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August Edition 2021

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A Comparative Study of Intelligent Control System Tuning Methods for an Evaporator based on Genetic Algorithm

Hala A. Abdel-Halim, Othman E. A., A. A. Sakr, A. A. Zaki, A. A. Abouelsoud. Published in Artificial Intelligence

International Journal of Applied Information Systems
Year of Publication: 2017
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: D. Asir Antony Gnana Singh, A. Escalin Fernando, E. Jebamalar Leavline
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  1. Hala A Abdel-Halim, Othman E A., A A Sakr, A A Zaki and A A Abouelsoud. A Comparative Study of Intelligent Control System Tuning Methods for an Evaporator based on Genetic Algorithm. International Journal of Applied Information Systems 11(10):1-14, February 2017. URL, DOI BibTeX

    	author = "Hala A. Abdel-Halim and Othman E. A. and A. A. Sakr and A. A. Zaki and A. A. Abouelsoud",
    	title = "A Comparative Study of Intelligent Control System Tuning Methods for an Evaporator based on Genetic Algorithm",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "February 2017",
    	volume = 11,
    	number = 10,
    	month = "Feb",
    	year = 2017,
    	issn = "2249-0868",
    	pages = "1-14",
    	numpages = 14,
    	url = "",
    	doi = "10.5120/ijais2017451646",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


This paper employs Genetic Algorithm to obtain the optimum parameters of an evaporator control system by using different tuning methods. Tuning methods consists of two main groups; first group consists of minimizing the performance indices factors separately such as; Integral of Absolute Error (IAE), Integral of Square Error (ISE), Integral of Time Absolute Error (ITAE) and Integral of Time multiplied with Square Error (ITSE).Second group consists of minimizing the performance indices factors separately plus the step response parameters such as; the rise Time (Tr), Settling Time (Ts), The Maximum Overshoot (Mp) and Steady state Error(Ess). Simulation Results prove that the second group of tuning methods give best performance, robust stability and improve the system robustness.


  1. Bansal, H.O., Sharma, R., and Shreeraman, P. 2012. PID controller tuning techniques: a review. J Control Eng Technol.; 2 (4):168–176.
  2. Panda, S. 2011. Differential evolution algorithm for SSSC-based damping controller design considering time delay. J Franklin Inst., 348(8):1903–1926.
  3. Mohamed, A.W., Sabry, H.Z., and Khorshid M. 2012. An alternative differential evolution algorithm for global optimization. J Adv Res.,3(2):149–165.
  4. Maldonado, L. B., Arias, H. P., Romero , F. A., and Granda, J.C., " Intelligent systems applied to the control of a distilling binary column", 2016 IEEE International Conference on Automatica (ICA-ACCA),2016,Pages: 1 - 9, IEEE Conference Publications
  5. Poongodi, P., Madhusudhanan, R. and Prema, N., " Implementation of Temperature Process Control using Soft Computing Techniques", proceedings of the World Congress on Engineering 2016, Vol I WCE 2016, June 29 - July 1, 2016, London, U.K.
  6. Pamela, D., and Jebarajan, T., "Intelligent Controller for Temperature Process", International Journal of Control and Automation, 2013, Vol.6, No.5, pp.191-198
  7. Lakshmi Narayana, K. V., Kumar, V. N., Dhivya,M. and Prejila Raj, R., "Application of Ant Colony Optimization in Tuning a PID Controller to a Conical Tank", Indian Journal of Science and Technology, January 2015,Vol 8(S2), 217–223,
  8. Jagatheesan, K., Anand, B., and Omar, M., "Design of Proportional - Integral - Derivative controller using Ant Colony Optimization technique in multi-area Automatic Generation Control", International Journal on Electrical Engineering and Informatics, December 2015, Vol. 7, No. 4.
  9. Jagatheesan, K. , Anand, B. , Dey, N. , Gaber, T., Hassanien, A. , Kim, T. , " A Design of PI Controller using Stochastic Particle Swarm Optimization in Load Frequency Control of Thermal Power Systems", 2015 Fourth International Conference on Information Science and Industrial Applications (ISI), 2015,p.p 25 – 32, IEEE Conference Publications
  10. Miavagh, F M. , Miavaghi, E. A. A. , Ghiasi, A. R. , Asadollahi, M. , "Applying of PID, FPID, TID and ITID controllers onAVR system using particle swarm optimization (PSO)",2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI), IEEE Conference Publications
  11. Noshahri, H.,and Kharrati, H., "PID controller design for unmanned aerial vehicle using genetic algorithm", 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE), 2014, p.p 213 – 217, IEEE Conference Publications
  12. Mohammed, N. F., Xiuzhen, M., and Enzhe, S., "Tuning of PID controller for diesel engines using genetic algorithm", 2013 IEEE International Conference on Mechatronics and Automation, 2013, p.p 1523 – 1527, IEEE Conference Publications
  13. Mohammed, N. F., Xiuzhen, M., and Enzhe, S.; Xiuzhen, M.; Hayat, Q., "Tuning of PID controller of synchronous generators using genetic algorithm”, 2014 IEEE International Conference on Mechatronics and Automation, (2014) 1544 – 1548, IEEE Conference Publications
  14. Patil, U., Katkol, P., and Havagondi, M., Patil, A., "Genetic algorithm approach for controlling nonlinear systems", 2014 International Conference on Circuits, Power and ComputingTechnologies (ICCPCT)-2014],p.p 944 -949, IEEE Conference Publications
  15. Ogata. K, 2009. Modern Control Engineering. 5th edition, Prentice-Hall International.
  16. Krohling, R.A., Rey, J.P. 2001. Design of optimal disturbance rejection PID controllers using genetic algorithms. IEEE Trans Evol Comput. ; 5(1):78–82.
  17. Yegiireddy, N. K.,and Panda, S., "Design and Performance analysis of PID controller for an AVR system using multi-objective non-dominated shorting genetic algorithm-II", 2014 International Conference on Smart Electric Grid (ISEG), 2014, p.p 1-7, IEEE Conference Publications
  18. Marzaki, M. H. , Tajjuddin, M., Rahiman, M. H. F., and Adnan, R., "Performance of FOPI with Error filter Based on Controllers Performance Criterion (ISE, IAE and ITAE) ", 2015 10th Asian Control Conference (ASCC), 2015, p.p 1-5, IEEE Conference Publications
  19. Chandrasekar, P., and Ponnusamy, L., "Passivity based level controller design applied to a nonlinear SISO system", 2013 International Conference on Green Computing, Communication and Conservation of Energy(ICGCE), 2013, p.p 392-396, IEEE Conference Publications
  20. Pan, F., Liao, H., Luo, J., and Xue, Y., "ITAE-Optimal PI Controller Based on Genetic Algorithm for Low-order Process with Large Time Delays", 2014 20th International Conference on Automation and Computing , 2014, p.p 143-139, IEEE Conference Publications
  21. Maiti, D., Acharya, A., Chakraborty, M., Konar, A.and Janarthanan, R., "Tuning PID and PI?Dd Controllers using the Integral Time Absolute Error Criterion",2008 4th International Conference on Information and Automation for Sustainability, 2008,p.p 457-462, IEEE Conference Publications
  22. Pitteea, A. V., Ah King, R. T. F., and Rughooputh, H. C. S., "Intelligent Controller for Multiple-Effect Evaporator in the Sugar Industry", 2004 IEEE International Conference on Industrial Technology (ICIT '04), 2004, Vol. 3, p.p 117-182 , , IEEE Conference Publication
  23. Yang, Q., Fu, S., Xue, Y., Ruan, S., and Chen, J., "Individual Intelligence Based Optimization and ITS Application to ITAE Standards Forms", 2014 10th International Conference Computational Inelligence and Security, 2014, p.p 109-113, IEEE Conference Publication
  24. Nagrath, I.J., and Gopal, M., 2007. Control Systems Engineering. Fifth Edition, ISBN: 81-224-2008-7, New Age International Publishers.
  25. Krohling, R.A., Rey, J.P., 2001. Design of optimal disturbance rejection PID controllers using genetic algorithms. IEEE Trans Evol Comput., 5(1):78–82.
  26. Newell, R. B. and Lee, P. L., 1989.Applied Process Control: A case study. Prentice-Hall of Australia Ltd.
  27. MatlabR2.14a (, 32bit (win32), Febrauary 11, 2014.
  28. Haupt, R. L., and Haupt, S. E., 2004. Practical Genetic Algorithms. 2nd Edition, John Wiley &Sons,Inc.
  29. Mirzal, A., Yoshii, S., and Furukawa, M., "PID Parameters Optimization by Using Genetic Algorithm", STECS Journal, 2006, Vol. 8, pp. 34-43.
  30. Stefani, R. T., Shahian B., and Savant, C. J., 2002. Design of Feedback Control Systems. 4th edition, New York, Oxford, Oxford University Press.
  31. Béla G. Lipták, 2013. Process Control: Instrument Engineers' Handbook. Butterworth-Heinemann, Technology & Engineering


Forced circulation evaporator, Genetic algorithm, Performance indices