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All Journal TEKNIK Jurnal Pendidikan Teknologi dan Kejuruan Indonesian Journal of Electrical Engineering and Informatics (IJEEI) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JST ( Jurnal Sains Terapan ) JURNAL INTEGRASI J-Dinamika: Jurnal Pengabdian Kepada Masyarakat JEECAE (Journal of Electrical, Electronics, Control, and Automotive Engineering) Jurnal Teknik Mesin dan Mekatronika (Journal of Mechanical Engineering and Mechatronics) Jurnal Rekayasa elektrika

Hary Oktavianto

Departemen Teknik Elektro, Politeknik Elektronika Negeri Surabaya

Author-ID : 2569500

Automotive Engineering Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Transportation Other

Published : 17 Documents Claim Missing Document

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Desain dan Simulasi Double Field Induction Generator (DFIG) dengan Software MATLAB Apriyanto, R. Akbar Nur; Purwanto, Era; Oktavianto, Hary; Prabowo, Gigih; Fakhruddin, Hanif Hasyier; Basuki, Gamar
JEECAE (Journal of Electrical, Electronics, Control, and Automotive Engineering) Vol 5, No 1 (2020): JOURNAL OF ELECTRICAL, ELECTRONICS, CONTROL, AND AUTOMOTIVE ENGINEERING (JEECAE)
Publisher : Politeknik Negeri Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32486/jeecae.v5i1.495

Perkembangan teknologi sangat berimplikasi pada kebutuhan energi listrik yang semakin meningkat. Kebutuhan energi listrik menjadi diskursus pembahasan seiring dengan ketersediaan energi listrik yang diprediksi tidak akan mampu memenuhi pasokan kebutuhan. Oleh karenanya diperlukan adanya pemanfaatan energi baru dan terbarukan dalam rangka memenuhi kebutuhan energi listrik tersebut. Energi angin yang merupakan salah satu energi baru terbaruakan yang dapat diproyeksikan menjadi energi alternatif, memiliki peluang besar dalam mambantu memenuhi kebutuhan energi listrik. Terlebih energi ini sangat mudah didapatkan dalam zonasi yang dekat dengan laut. Salah satu poin krusial dalam pemanfaatan energi angin untuk direalisasikan pada pembangit listrik tenaga angin adalah DFIG (Double-Field Induction Generator). DFIG diperlukan desain yang baik untuk mendapatkan energi angin maksimum sebelum didistribusikan ke konsumen. Pada penelitian ini membahas desain dan simulasi DFIG (Double Field Induction Generator) Wind Energy. Penelitian ini dilakukan secara simulasi pada Simulink Matlab dengan memodelkan secara matematik DFIG dari equivalent circuit.

Metode Kontrol Skalar Dengan Penala Parameter PID Otomatis Menggunakan Algoritma PSO Sebagai Pengendali Kecepatan Motor Induksi Tiga Fasa Berbasis LabView R. Akbar Nur Apriyanto; Era Purwanto; Hary Oktavianto; Gigih Prabowo
JST (Jurnal Sains Terapan) Vol 6, No 1 (2020): JST (Jurnal Sains Terapan)
Publisher : Pusat Penelitian dan Pengabdian kepada Masyarakat, Politeknik Negeri Balikpapan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32487/jst.v6i1.814

This paper presents the PID parameter tuning automatically for three-phase induction motors with the V/F control method or scalar control. PID control is one type of simple control, its computation is light, easy to implement and known to be tough in dealing with disturbances. But PID has a weakness that is the difficulty of determining the optimal PID parameters, especially when applied to nonlinear systems such as speed control on a scalar control-based induction motor. Output tuning results automatically in the form of the best PID parameter data collection. This study was validated through simulations using the LabView application by testing dynamic speeds and dynamic loads. When testing using the automatic tuning algorithm PID parameters with parameters that have been optimized the Particle Swarm Optimization (PSO) algorithm, the dynamic speed performance characteristic results are better seen from the transient time in the form of average dead time and rise time of less than 1ms. The results of the Global Best Fitness from the PID automatic tuning simulation using the LabView-based PSO algorithm in the form of Kp, Ki, and Kd values can be used as input for setting the speed of the induction motor in real time.Keywords : autotuning, speed control, induction motor, Particle Swarm Optimization , LabVIEW®ABSTRAKPada tulisan ini menyajikan penala parameter PID secara otomatis untuk motor induksi tiga fase dengan metode kendali V/F atau kendali skalar. Kendali PID merupakan salah satu tipe kendali sederhana, komputasinya ringan, mudah diimplementasi dan dikenal tangguh menghadapi gangguan. Tetapi PID memiliki kelemahan yaitu sulitnya menentukan parameter PID yang optimal, apalagi bila diterapkan pada sistem non-linear seperti pengendalian kecepatan pada motor induksi berbasis kendali skalar. Luaran hasil penalaan secara otomatis berupa kumpulan data parameter PID terbaik. Penelitian ini divalidasi melalui simulasi menggunakan aplikasi LabView dengan pengujian kecepatan dinamik dan beban dinamik. Ketika pengujian menggunakan parameter PID algoritma penala otomatis dengan parameter yang telah dioptimalkan algoritma Particle Swarm Optimization (PSO), didapatkan hasil karakteristik performa kecepatan dinamik yang lebih baik dilihat dari waktu transien berupa rata-rata dead time dan rise time kurang dari 1ms. Hasil Global Best Fitness dari simulasi penalaan otomatis PID menggunakan algoritma PSO berbasis LabView yang berupa nilai Kp, Ki, dan Kd dapat dijadikan input untuk pengaturan kecepatan motor induksi secara real time.Kata kunci : penala otomatis, pengatur kecepatan, motor induksi, Particle Swarm Optimization, LabVIEW®

Surface 3D Scanner Using Time of Flight Ranging Sensor with Cylindrical Coordinate System Achmad Purnomo Wijaya; Niam Tamami; Hary Oktavianto
Jurnal Teknik Mesin dan Mekatronika (Journal of Mechanical Engineering and Mechatronics) Vol 7, No 1 (2022): JOURNAL OF MECHANICAL ENGINEERING AND MECHATRONICS
Publisher : President University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/jmem.v7i1.1477

3D scanner that uses image sensors requires the role of a computer that includes a data generator, data acquisition, and visual display. In a simply system, it can be designed the sensory system uses non-imagery sensor so the role of the data generator can be handled by the microcontroller. This research aims to make a simple 3D scanner using inexpensive non-imagery Time of Flight VL53L0X sensor and data processing can be processed directly by the microcontroller. The results of sensor distance measurements are processed on the microcontroller and desktop application. The distance and angle values are converted into Cartesian coordinate using cylindrical coordinate system. The scan results of the cubes, prisms and cylinder are similar with the reference object, but the results of the pyramid test at the top cannot be scanned properly due to the narrow surface. The laser beam from the emitter cannot bounce back to the collector properly makes distance reading is inaccurate and causes error in the point cloud conversion. The comparison error between the side of the scan results and the reference object is between 2.54-39.8%. The surface of objects with bright color has a smaller error than those with dark color. The comparison error of the height of the scan results with the reference object is between 5-32%. The angle of the emitter exclusion cone and the collector exclusion cone sensor affects the error at the side and height of the scan results.

Responsive Motion Control for Robot Soccer Navigation Using Adaptive Social Force Framework Bima Sena Bayu Dewantara; Bagus Nugraha Deby Ariyadi; Hary Oktavianto
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 3: September 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/.v9i3.2859

This paper presents a modified Social Force Model (SFM) for navigation control of a soccer robot application. We modified the way of determining the parameter value of the gain factor, , of the SFM using the Fuzzy Inference System (FIS), so that the value of the gain factor, , is adaptive. The purpose of the gain factor adaptation is that the robot can move responsively but not over-reactive when it encounters an obstacle at high speed, which is a weakness of SFM with fixed parameters. Modification of SFM parameters using FIS is hereinafter referred to as the Fuzzy-based Social Force Model (F-SFM). We used this technique on a soccer robot with an omnidirectional drive platform with three motors. As an experiment, several modifications to the FIS rules were made and compared to the SFM with fixed parameters. The simulation-based experimental results show that the proposed method outperforms the SFM method with fixed-parameters, and the computation time does not differ significantly so that it can be applied for real implementation.

Aplikasi Direct Matrix Converter pada Pengendali Kecepatan Motor Induksi 3 Fase menggunakan Modulasi Venturini GAMAR BASUKI; ERA PURWANTO; HARY OKTAVIANTO; MENTARI PUTRI JATI; MOCHAMAD ARI BAGUS NUGROHO
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 8, No 3 (2020): ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektro
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v8i3.518

ABSTRAKMotor induksi yang paling banyak digunakan juga memiliki kekurangan seperti losses yang cukup tinggi, power factor correction, dan efisiensi yang rendah. Oleh karena itu, dibutuhkan pengendali motor induksi yang memiliki performa dan efisiensi yang tinggi. Salah satu jenis AC – AC konverter yang mempunyai efisiensi, lifetime, kekompakan dan faktor daya mendekati unity yang akan digunakan sebagai pengendali motor induksi adalah matrix converter. Metode venturini digunakan sebagai modulasi pada matrix converter. Untuk itu dalam penelitian ini dilakukan pembuatan simulasi menggunakan simulink MATLAB dan hardware matrix converter. Pengujian matrix converter menggunakan modulasi venturini sebagai pengendali motor induksi telah dilakukan dengan motor dapat berputar mencapai kecepatan nominal sebesar 1440 Rpm sesuai nameplate dan motor juga dapat berputar dibawah frekuensi nominal. Dengan penelitian ini, pengendalian motor induksi dapat lebih efisien dalam penggunaannya di berbagai bidang.Kata kunci: Matrix converter, metode venturini, motor induksi. ABSTRACTThe most widely used induction motors also have disadvantages such as fairly high losses, power factor correction, and low efficiency. From this disadvantages, we need an induction motor controller that has high performance and efficiency. One type of AC-AC converter that has efficiency, lifetime, compactness and power factor approach to unity that will be used as an induction motor controller is a matrix converter. The Venturini method is used as modulation in the matrix converter. For this reason, in this study, simulation was made using MATLAB simulink and hardware matrix converter. Matrix converter testing using venturini modulation as an induction motor controller has been done with the motor can be rotate reaching a nominal speed of 1440 Rpm according to nameplate and the motor can also rotate below the nominal frequency. It is expected that induction motor controller can be more efficient in their use in various fields.Keywords: Matrix converter, venturini method, induction motor

Kendali Kecepatan Motor Induksi 3 Fase Berbasis Particle Swarm Optimization (PSO) HANIF HASYIER FAKHRUDDIN; HANDRI TOAR; ERA PURWANTO; HARY OKTAVIANTO; RADEN AKBAR NUR APRIYANTO; ANGGA WAHYU ADITYA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 8, No 3 (2020): ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektro
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v8i3.477

ABSTRAKMotor induksi secara struktur dan kendali standarnya dirancang untuk bekerja pada kecepatan nominal, sehingga sulit mengendalikan kecepatan sesuai kebutuhan karena akan mengubah konstruksi motor. Penelitian tentang pengendalian motor induksi agar semudah mengendalikan motor DC sudah banyak dilakukan oleh peneliti, salah satunya adalah dengan kendali skalar. Kendali skalar banyak digunakan karena memiliki keunggulan sederhana, biaya murah, mudah didesain dan diimplementasikan, serta yang paling penting tidak memerlukan parameter dari motor induksi. Penggunaan kendali skalar yang telah dilengkapi pengendali PID penalaan otomatis, dengan parameter yang telah dioptimalkan algoritma Particle Swarm Optimization (PSO), akan memudahkan pengendalian kecepatan motor induksi tiga fase pada kecepatan beragam. Simulasi penalaan otomatis PID menggunakan PSO telah dilakukan dengan LabView, dengan karakteristik maksimal 10% overshoot, 1% error steady state dan rise time kurang dari 2 milidetik. Sementara dalam pengujian real time dengan MyRIO hasilnya tanpa overshoot, 5.5% error steady state maksimal dan rise time maksimal 5 detik.Kata kunci: Kendali skalar, PID, Particle Swarm Optimization, LabView ABSTRACTInduction motor is designed at nominal speed as default, we have to change its stucture to obtain dessired speed. Many researchers developt method how to control induction motor as simple as DC motor, one of the methods is scalar control. Scalar control has several benefits, such as simply, low cost, easily designed and implemented, and the main banefit is no necessary motor parameters. Using scalar control with PID controller that optimized Partical Swarm Optimization (PSO) algoritm, will ease to control 3 phase induction motor variant speed. Simulation auto tunning using PSO has done on LabView, it has some characteristic, they are 10% overshoot, 1% steady state error, and rise time within 2ms. In other hand, real time test using MyRIO got no overshoot, 5.5% steady state error maximal, and rise time maximal 5 s characteristic.Keywords: Scalar control, PID, Particle Swarm Optimization, LabView

Strategi Implementasi Adaptive Neuro Fuzzy Inference System (ANFIS) pada Kendali Motor Induksi 3 Fase Metode Vektor-Tidak Langsung HANIF HASYIER FAKHRUDDIN; HANDRI TOAR; ERA PURWANTO; HARY OKTAVIANTO; GAMAR BASUKI; RADEN AKBAR NUR APRIYANTO; ABDILLAH AZIZ MUNTASHIR
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 9, No 4 (2021): ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektro
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v9i4.786

ABSTRAKKendali vektor merupakan solusi terbaik dalam kendali motor induksi untuk meningkatkan karakter dinamis dan efisiensinya. Pada penelitian ini, sebuah kendali kecepatan PID dipadukan dengan Adaptive Neuro Fuzzy Inference System (ANFIS) untuk meningkatkan keandalan pada berbagai kecepatan acuan. Metode cerdas Particle Swarm Optimization (PSO) digunakan untuk optimasi dataset ANFIS. Pengujian keandalan dilakukan dengan membandingkan PID konvensional dengan PID-ANFIS pada motor induksi 3 fase berdaya 2HP. Validasi penelitian dilakukan melalui simulasi di platform LabView. PID-ANFIS membuktikan hasil yang jauh lebih baik dari kendali PID konvensional pada berbagai kecepatan acuan. Pemilihan rise time tercepat sebagai fungsi fitness menghasilkan kendali yang memiliki dead time dan rise time 1.5x lebih cepat. PID-ANFIS berhasil menghilangkan undershoot dan osilasi steady state ketika uji kecepatan tinggi.Kata kunci: Kendali Vektor, Adaptive Neuro Fuzzy Inference System, Particle Swarm Optimization, LabView ABSTRACTVector control is the best solution in induction motor control to enhance its dynamic character and efficiency. In this research, a PID speed controller is combined with the Adaptive Neuro-Fuzzy Inference System (ANFIS) to enhance reliability at various reference speeds. The intelligent method Particle Swarm Optimization (PSO) is used to optimize the ANFIS dataset. Reliability testing is done by comparing conventional PID with PID-ANFIS on a 2HP 3-phase induction motor. The research validation was carried out through a simulation on the LabView platform. The PID-ANFIS proved significantly better results than conventional PID control at a wide range of reference speeds. Selection of the fastest rise time as a fitness function results in a control that has a dead time and a rise time of 1.5x faster. PID-ANFIS successfully negates undershoot and steadystate oscillations during high-speed tests.Keywords: Vector Control, Adaptive Neuro Fuzzy Inference System, Particle Swarm Optimization, LabView

PENGENDALIAN MOTOR INDUKSI 3 FASA DENGAN BEBAN DINAMIS KONTROL PID FUZZY MENGGUNAKAN METODE FOC-TAK LANGSUNG (INDIRECT FIELD ORIENTED CONTROL) PADA LABVIEW R. Oktav Yama Hendra; Era Purwanto; Hary Oktavianto; Abdillah Aziz Muntashir; Kadek Reda Setiawan Suda
Jurnal Pendidikan Teknologi dan Kejuruan Vol. 19 No. 1 (2022): Edisi Januari 2022
Publisher : Universitas Pendidikan Ganesha

This research includes the design of a PID speed control simulation combined with Fuzzy Logic Control as a control, and increasing the speed performance of an induction motor in LabView. The control method used is a vector control induction motor, namely Field Oriented Control. This method can set up an induction motor as easily as a separate amplifier DC motor. Fuzzy Logic Control with its advantages acts as a scheduler for the PID value with the advantage of increasing the dynamic performance of the induction motor against changes in load and speed changes. From several simulations carried out on LabView with 5nm and 9nm dynamic loads using the FOC method, the average risetime result is 80% fast. When testing the dynamic load control performance, the results of the PID-Fuzzy method are better than conventional PID, especially at high motor speeds and nominal loads. In dynamic load testing, PID-Fuzzy is also better than conventional PID. With a conventional PID controller when the load is 9nm with a set point of 1500 RPM, the risetime is 10.0 ms and the steady error is 1.8%. With the PID-Fuzzy method, a risetime of 6.6 ms is obtained and a steady error of 0.7.

DESAIN KONTROL KECEPATAN MOTOR INDUKSI TIGA FASA MENGGUNAKAN FUZZY PID BERBASIS IDIRECT FIELD ORIENTED CONTROL Ridwan Ridwan; Era Purwanto; Hary Oktavianto; Muhammad Rizani Rusli; Handri Toar
JURNAL INTEGRASI Vol 11 No 2 (2019): Jurnal Integrasi - Oktober 2019
Publisher : Politeknik Negeri Batam

Motor induksi tiga fasa (MITF) umumnya digunakan di berbagai aplikasi di industri karena keandalannya, biaya rendah, kontruksi kokoh, perawatan rendah, dan effisiensi yang tinggi. Namun untuk mengontrol MITF tidak semudah seperti mengontrol motor DC, karena MITF merupakan motor yang tidak linear. Penggunaan metode indirect field oriented control (IFOC) dengan kontroler fuzzy proportional integrator and derivative (FPID) dipilih untuk dapat mengatur kecepatan MITF. Metode IFOC akan membuat MITF dapat dikontrol seperti motor DC penguat terpisah. Kontroler FPID yang di desain dengan mengganti kontroler PID konvensional. Performa kontroler FPID yang di desain dibandingkan dengan kontroler PID konvensional. Performa respon yang dibandingkan seperti rise time, settling time, overshoot, steady state error, dan undershoot. Hasil simulasi yang dibuat menunjukkan bahwa dengan menggunakan kontroler FPID lebih baik dibandingkan dengan kontroler PID. Dimana respon overshoot untuk kontroler FPID 0% sedangkan kontroler PID adalah 0.23%. Begitu pula dengan respon undershoot untuk kontrol FPID adalah 2.88% sedangkan kontroler PID adalah 6.78%. Untuk respon rise time, settling time, dan steady state error tidak jauh berbeda dari kedua kontroler. Sistem yang sudah di buat disimulasikan di platform LabView

PENALA PARAMETER PID OTOMATIS PADA PENGATUR KECEPATAN MOTOR INDUKSI TIGA FASA Handri Toar; Era Purwanto; Hary Oktavianto; Ridwan Ridwan; Muhammad Rizani Rusli
JURNAL INTEGRASI Vol 12 No 1 (2020): Jurnal Integrasi - April 2020
Publisher : Politeknik Negeri Batam

PID is one of the simple controller, fast computing, easy to implement, reliable to face the disturbance especially to handle the linear system. Meanwhile induction motor is one of a high nonlinear system. Is PID can handle the induction motor. Therefore PID controller enhancement is needed. The controller has the ability to tune up the parameter while running. To tune-up, the controller needs a bunch of collections of parameters PID that ready to use. If we use the manual way to collect like trial and error, it will consume much power and time. And not all systems can be used the Ziegler-Nichols method. This research offering an algorithm for the autotuning PID parameter to control the speed of induction motor based on vector control to collect the PID parameter automatically. After validation by using LabVIEW simulation, the system provides a good speed response without overshoot when the speed increased and without undershoot when the speed decreased.

Co-Authors Abdillah Aziz Muntashir ABDILLAH AZIZ MUNTASHIR Abdullah Aziz Muntashir Achmad Purnomo Wijaya Amang Sudarsono, Amang angga wahyu aditya Apriyanto, R. Akbar Nur Bagus Nugraha Deby Ariyadi Bambang Sumantri BASUKI, GAMAR Bima Sena Bayu Dewantara Dadet Pramadihanto Era Purwanto Fakhruddin, Hanif Hasyier Fatekha, Rifqi Amalya Gamar Basuki GAMAR BASUKI Gigih Prabowo Handri Toar Hanif Hasyier Fakhruddin HANIF HASYIER FAKHRUDDIN HANIF HASYIER FAKHRUDDIN Idris Winarno Jati, Mentari Putri Kadek Reda Setiawan Suda Kadek Reda Setiawan Suda Kisron Kisron MOCHAMAD ARI BAGUS NUGROHO Niam Tamami R. Akbar Nur Apriyanto R. Akbar Nur Apriyanto R. Akbar Nur Apriyanto R. Oktav Yama Hendra RADEN AKBAR NUR APRIYANTO RADEN AKBAR NUR APRIYANTO Ridwan Ridwan Rusli, Muhammad Rizani Sri Muntiah Andriami Wahjoe Tjatur Sesulihatien

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