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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
10.5120/ijais2017451646
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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

    @article{10.5120/ijais2017451646,
    	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 = "http://www.ijais.org/archives/volume11/number10/966-2017451646",
    	doi = "10.5120/ijais2017451646",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

Abstract

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.

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Keywords

Forced circulation evaporator, Genetic algorithm, Performance indices