Optimization of a DC Motor Drive Using a Firefly Algorithm

Klempka, R.; Filipowicz, B.

doi:10.1109/isem.2018.8442512

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…Firefly algorithm (algoritma firefly) pertama kali di kemukakan oleh Xin She Yang pada tahun 2008 dan 2010 [8]- [10]. Firefly algorithm digunakan untuk memecahkan suatu permasalahan tertentu secara sistematis berdasarkan sifat dan karakter kunang-kunang.…”

Section: Firefly Algorithmunclassified

Kontrol Kecepatan Motor BLDC dengan PID - Firefly

Triwijaya¹,

Prasetyo

Wati

2021

Media Komunikasi Teknologi

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Conventional DC motors often experience problems that require regular maintenance. The use of conventional DC motors can be replaced with Brushless DC (BLDC) motors. This BLDC motor has good efficiency and durability. Increasing the ability of BLDC motors can be done by speed regulation using the Proportional-Integral-Derivative (PID) method combined with Firefly Algorithm. Testing this method uses matlab 2014a. The firefly algorithm can obtain parameter values of Kp, Ki, and Kd which are then used as PID input. Because of inaccuracies in determining the value of a constant in PID and can cause the length of time to reach the desired speed. BLDC motor speed regulation with the PID method combined with firefly algorithm can make the BLDC motor reach synchronous faster.

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Section: Firefly Algorithmunclassified

Kontrol Kecepatan Motor BLDC dengan PID - Firefly

Triwijaya¹,

Prasetyo

Wati

2021

Media Komunikasi Teknologi

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“…So, it is difficult to adjust the parameters, and it takes a long time and also the control accuracy is not good [5]. In recent years, researchers have used many artificial intelligent methods to optimize the parameters of DC motors, such as particle swarm optimization algorithm [6]− [8], Harris Hawks optimization [9], [10], genetic algorithm [11]− [13], firefly algorithm [14]− [16], flower pollination algorithm [17]− [19] and neural network [20]− [21].…”

Section: Introductionmentioning

confidence: 99%

Optimization of PID parameters for controlling DC motor based on the aquila optimizer algorithm

Aribowo

Supari

Suprianto

2022

IJPEDS

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This study presents the application of the aquila optimizer (AO) algorithm to determine the parameters of the proportional integral derivative (PID) controller to control the speed of a dc motor. The AO method is inspired by the most popular bird of prey in the northern hemisphere named Aquila. Initially, the proposed AO algorithm is applied to unimodal and multimodal benchmark optimization problems. To get the performance of the AO method, the controller is compared with other methods, namely Seagull optimization algorithm (SOA), marine predators algorithm, giza pyramids construction (GPC), and chimp optimization algorithm (ChOA). The results represent that the AO is promising and shows the effectiveness. Determination of PID parameters using the AO method for dc motor speed control system shows superior performance.

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Modification of the Firefly Algorithm for Improving Solution Speed

Klempka

2020

Advances in Intelligent Systems and Computing

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Optimization of a DC Motor Drive Using a Firefly Algorithm

Cited by 3 publications

References 16 publications

Kontrol Kecepatan Motor BLDC dengan PID - Firefly

Kontrol Kecepatan Motor BLDC dengan PID - Firefly

Optimization of PID parameters for controlling DC motor based on the aquila optimizer algorithm

Modification of the Firefly Algorithm for Improving Solution Speed

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