Optimisasi Sistem Kontrol Kecepatan Motor BLDC Berbasis Aritificial Intelligence

Anshory, Izza (2021) Optimisasi Sistem Kontrol Kecepatan Motor BLDC Berbasis Aritificial Intelligence. Doctoral thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Motor Brushless Direct Current (BLDC) telah banyak digunakan dalam dunia industri transportasi, salah satunya sebagai penggerak kendaraan sepeda listrik. Aspek penting dalam bagian penggerak motor BLDC sepeda listrik adalah kontrol kecepatan. Sistem kontrol kecepatan diimplementasikan untuk mengurangi sumber gangguan yang muncul, sehingga mempengaruhi kecepatan dan kestabilan. Indikator kestabilan adalah berkurangnya error steady state dan meningkatnya respon transient. Tujuan penelitian ini adalah melakukan optimisasi pada sistem kontrol kecepatan motor BLDC yang digunakan sebagai bagian penggerak sepeda listrik dengan menggunakan beberapa metodologi kontrol modern.
Metodologi yang digunakan dalam penelitian ini adalah melakukan pemodelan matematika motor BLDC melalui identifikasi sistem sehingga didapatkan fungsi alih. Identifikasi sistem yang digunakan untuk mendapatkan fungsi alih ini yaitu struktur model Auto Regressive Exogenous (ARX). Setelah didapatkan model matematika dalam bentuk fungsi alih, dilakukan optimisasi dengan menggunakan kontrol cerdas berbasis artificial intelligence. Algoritma artificial intelligence yang diusulkan dalam penelitian ini adalah algoritma modifikasi firefly, kemudian hasilnya dibandingkan dengan algoritma Particle Swarm Optimization (PSO Algorithm), dan fuzzy logic.
Berdasarkan hasil pengukuran dan simulasi, diperoleh beberapa hasil penelitian, pertama persamaan matematika motor BLDC dalam bentuk fungsi alih. Hasil kedua adalah nilai respon transien untuk optimisasi menggunakan algoritma modifikasi firefly ketika disimulasikan pada sistem kontrol kecepatan motor BLDC yaitu pada saat tidak ada beban, nilai rise timenya adalah 0.009931 detik, nilai settling time 0.984 detik, dan nilai overshoot 0.654%. Sedangkan pada saat diberi beban nilai respon transien yang diperoleh adalah rise time 0.0126 detik, settling time 0.0563 detik, dan nilai overshoot 0.396 %. Sedangkan untuk nilai performansi ITAE nya sebesar 3.3352e+06.
Keywords : Motor BLDC, Identifikasi Sistem, PID, Fuzzy Logic, Algoritma PSO, Modifikasi Algoritma Firefly.
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Brushless Direct Current (BLDC) motors are widely used in the transportation industry, one of which is to drive electric bicycles. An important aspect of the driving part of the BLDC electric bike is speed control. A speed control system is implemented to reduce the source of the disturbance that appears, thus affecting speed and stability. Stability can be obtained by designing the right controller to be applied to the BLDC motor plant. Not every BLDC motor plant available on the market, the manufacturer provides several mechanical and electronic parameters. The purpose of this research is to optimize the BLDC motor speed control system that is used as a driving part of an electric bicycle using several modern control methodologies to increase stability indicators, such as the value of rise-time, settling time, and reduce overshoot values.
The methodology used in this research is to perform mathematical modeling of the BLDC motor through system identification to obtain the transfer function. The system identification is used to obtain this transfer function as the Auto Regressive Exogenous (ARX) model structure. After getting a mathematical model in the form of a transfer function, optimization carried out using intelligent control based on artificial intelligence. The artificial intelligence algorithm proposed in this study is the modified firefly algorithm, then the results are compared with the Particle Swarm Optimization (PSO Algorithm) algorithm and fuzzy logic.
Based on the results of measurement and simulation, several research results obtained, first the BLDC motor mathematical equation in the form of a transfer function. The second result is the transient response value for optimization using the modified firefly algorithm when simulated on a BLDC motor speed control system, namely, when there is no load, the rise time value is 0.009931 seconds, the settling time value is 0.984 seconds, and the overshoot value is 0.654%. Meanwhile, when given a load, the transient response values obtained were a rise time of 0.0126 seconds, settling time 0.0563 seconds, and an overshoot value of 0.396%. Meanwhile, the ITAE performance value is 3.3352e + 06.
Keywords : BLDC Motor, System Identification, PID, Fuzzy Logic, PSO algorithm PSO, Modified Firefly Algorithm

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Motor BLDC, Identifikasi Sistem, PID, Fuzzy Logic, Algoritma PSO, Modifikasi Algoritma Firefly.BLDC Motor, System Identification, PID, Fuzzy Logic, PSO algorithm PSO, Modified Firefly Algorithm
Subjects:	Q Science > QA Mathematics > QA336 Artificial Intelligence T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2681.O85 Electric motors, Brushless.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20001-(S3) PhD Thesis
Depositing User:	Izza Anshory
Date Deposited:	03 Mar 2021 02:05
Last Modified:	03 Mar 2021 02:05
URI:	http://repository.its.ac.id/id/eprint/83217

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