Widi Aribowo, Laith Abualigah, Diego Oliva, Aditya Prapanca
This article presents a modified method of mountain gazelle optimizer (MMGO) as a direct current (DC) motor control. Mountain gazelle optimizer (MGO) is an algorithm inspired by the life of the mountain gazelle animal in nature. This animal concept has five essential steps that are duplicated in mathematical modeling. This article uses two tests to get the performance of the MMGO method. The first test uses a benchmark function test with a comparison method, namely the sine tree seed algorithm (STSA) and the original MGO. The second test is the application of MMGO as a DC motor control. The simulation results show that MMGO can reduce the overshoot of conventional proportional integral derivative (PID) control by 0.447% and has a better integral time square error (ITSE) value of 5.345 than conventional PID control. Thus, the MMGO method shows promising performance. © 2024, Institute of Advanced Engineering and Science. All rights reserved.
Department of Electrical Engineering, Faculty of Vocational, Universitas Negeri Surabaya, Surabaya, Indonesia; Department of Computer Science, Al al-Bayt University, Mafraq, Jordan; Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan; MEU Research Unit, Middle East University, Amman, Jordan; Department of Electrical and Computer Engineering, Lebanese American University, Byblos, Lebanon; School of Computer Sciences, Universiti Sains Malaysia, Pulau Pinang, Malaysia; School of Engineering and Technology, Sunway University Malaysia, Petaling Jaya, Malaysia; Applied Science Research Center, Applied Science Private University, Amman, Jordan; Depto. de Ingeniería Electro-Fotónica, Universidad de Guadalajara, CUCEI, Guadalajara, Mexico; Department of Computer Engineering, Faculty of Engineering, Universitas Negeri Surabaya, Surabaya, Indonesia
