Modern Temperature Control of Electric Furnace in Industrial Applications Based on Modified Optimization Technique

Mahmoud M. Hussein, Salem Alkhalaf, Tarek Hassan Mohamed, Dina S. Osheba, Mahrous Ahmed, Ashraf Hemeida () and Ammar M. Hassan
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Mahmoud M. Hussein: Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt
Salem Alkhalaf: Department of Computer, College of Science and Arts in Ar-Rass, Qassim University, Ar Rass 52571, Saudi Arabia
Tarek Hassan Mohamed: Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt
Dina S. Osheba: Department of Electrical Engineering, Faculty of Engineering, Menoufia University, Shebin El Kom 32511, Egypt
Mahrous Ahmed: Department of Electrical Engineering, College of Engineering, Taif University, Taif 21944, Saudi Arabia
Ashraf Hemeida: Department of Electrical Engineering, Faculty of Energy Engineering, Aswan University, Aswan 81528, Egypt
Ammar M. Hassan: Arab Academy for Science, Technology and Maritime Transport, Aswan 81516, Egypt

Energies, 2022, vol. 15, issue 22, 1-12

Abstract: In this paper, an enhanced version of whale optimization algorithm (EWOA) is presented to be applied in adaptive control techniques as a parameter tuner. One weakness point in this control scheme is the low efficiency of its objective function. Balloon effect (BE) is a modification introduced to increase the efficiency of the objective function of the optimization method and the ability of the controller to deal with system problems increase consequently. Controlling of the temperature of electric furnaces is considered as one of the important issues in several industrial applications. Conventional controllers such as PID controller cannot deal efficiently with the problem of parameters variations and step disturbance. This paper proposes an adaptive controller, in which the gain of the temperature controller is tuned online using EWOA supported by balloon effect. System responses obtained by the proposed adaptive control scheme using EWOA + BE have been compared with an electric furnace temperature control (EFTC) scheme response using both the PID controller-based modified flower pollination algorithm (MoFPA) and PID-accelerated PIDA-based MoFPA. From the results, it can be observed that the proposed controller tuned by the EWOA + BE method improves the time performance compared with the other techniques (PID and PIDA-based MoFPA) in case of EFTC application.

Keywords: modern control methods; temperature control; electric furnace; industrial applications (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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