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All Journal Jurnal Listrik, Instrumentasi, dan Elektronika Terapan
Muhammad Rakha Firdaus
Departemen Teknik Elektro dan Informatika, Universitas Gadjah Mada
Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Identifikasi Sistem Motor DC dan Penerapan Kendali PID, LQR, dan Servo Tipe 1 Berbasis Arduino-MATLAB Muhammad Rakha Firdaus; Tegar Arif Berbudi; Salima Nurrahma; Galang Izzaulhaq; Imroatul Hudati
Jurnal Listrik, Instrumentasi, dan Elektronika Terapan Vol 4, No 1 (2023)
Publisher : Departemen Teknik Elektro dan Informatika Sekolah Vokasi UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/juliet.v4i1.81918

Abstract

Abstract – There has been a lot of research on the application of control to DC motors. However, there are often obstacles regarding the selection of controllers that are not appropriate, resulting in the control of DC motors becoming unstable. So to overcome this, a system identification process is needed on the DC motor. This paper will explain the process of identifying the DC motor coupling system using the System Identification Toolbox in MATLAB. After obtaining the modeling, several types of control will be applied, namely PID, LQR, and type-1 servo to be compared to determine effective control for the DC motor system. From the results of the system identification process, it is obtained that the system model closest to the reference model is the ARX model with a best-fit value of 63.2%. Furthermore, this ARX model will be used as a mathematical model of the system to which PID, LQR, and type-1 servo controls will be added. From the experimental results, it is found that the best type of control in this system is to use type-1 servo control which produces the smallest MSE value of 4.9897.Keywords – identification system, LQR, PID, type-1 servoIntisari – Penelitian mengenai penerapan kendali pada motor DC telah banyak dilakukan. Namun sering terjadi kendala mengenai pemilihan pengontrol yang tidak tepat sehingga mengakibatkan pengendalian motor DC menjadi tidak stabil. Sehingga untuk mengatasi hal ini, diperlukan suatu proses identifikasi sistem pada motor DC. Pada makalah ini menjelaskan proses identifikasi sistem kopling motor DC dengan menggunakan System Identification Toolbox pada MATLAB. Setelah mendapatkan pemodelan tersebut maka akan diterapkan beberapa macam kendali yaitu PID, LQR, dan servo tipe 1 untuk dibandingkan untuk menentukan kendali yang efektif untuk sistem motor DC tersebut. Dari hasil proses identifikasi sistem diperoleh bahwa model sistem yang paling mendekati dengan model referensi adalah model ARX dengan nilai best-fit sebesar 63,2%. Selanjutnya model ARX ini akan digunakan sebagai model matematis sistem yang akan ditambahkan kendali PID, LQR, dan servo tipe 1. Dari hasil percobaan didapatkan bahwa jenis kendali paling baik pada sistem ini adalah dengan menggunakan kendali servo tipe 1 yang menghasilkan nilai MSE paling kecil yaitu sebesar 4,9897.
Implementasi Kontrol PID pada Kopel Motor DC dengan Menggunakan Filter Kalman Salima Nurrahma; Tegar Arif Berbudi; Muhammad Rakha Firdaus; Galang Izzaulhaq; Imroatul Hudati
Jurnal Listrik, Instrumentasi, dan Elektronika Terapan Vol 4, No 1 (2023)
Publisher : Departemen Teknik Elektro dan Informatika Sekolah Vokasi UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/juliet.v4i1.82150

Abstract

This paper describes a DC motor clutch system that uses  control methods PID and uses a Kalman filter. The methods used aim to obtain stable results from the DC motor coupling system used. To get the appropriate results, several stages were carried out such as hardware design where this process was carried out by pairing all the components used including the power supply, DC motor driver, Arduino Uno, potentiometer and the two coupled DC motors. This system uses an input voltage of 12 V and will then be processed by the motor driver to drive the DC motor. Based on the results that have been obtained and the system response after being given control. It can be observed that when the system uses the Kalman filter and uses the PI control the system response results have a small steady state error.
Co-Authors Galang Izzaulhaq Imroatul Hudati Salima Nurrahma Tegar Arif Berbudi