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Aplikasi Metode Cerdas untuk Optimasi Controller PID Motor DC Berbasis Firefly Algorithm Djalal, Muhammad Ruswandi; Nurohmah, Hidayatul; Imran, Andi; Yunus, Muhammad Yusuf
JURNAL NASIONAL TEKNIK ELEKTRO Vol 6, No 2: Juli 2017
Publisher : Jurusan Teknik Elektro Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jnte.v6n2.393.2017

Controlling the speed of dc motor is very important to maintain the stability of motor operation. One of the most commonly used control methods is the proportional integral derivative (PID) controller. In order to operate optimally, PID controllers need the correct parameter tuning. One of the problems in using PID controllers is the determination of the proper PID parameters. In the determination of PID controller parameters is still done conventionally, so the performance of PID becomes not optimal. Therefore, in this research we will propose one of PID parameter tuning method by using intelligent method based on Firefly Algorithm (FA), to optimize and determine the proper parameters of PID. The FA is one of the smart methods inspired by firefly behavior that moves at night with flashing habits, which are then adapted and applied into intelligent algorithms to solve optimization problems. From the results obtained the Firefly method can well tune the PID parameters, so the resulting overshoot does not exist and settling time is very fast. As a comparison, in this study will also discuss the use of intelligent methods based on Bee Colony and Cuckoo Search.Keywords: PID, Bee-Colony, Cuckoo, Firefly, Settling timeAbstrak - Pengontrolan kecepatan motor dc merupakan hal yang sangat penting untuk menjaga stabilitas operasi motor. Salah satu metode pengontrolan yang sering digunakan adalah kontroler proportional integral derivative (PID). Agar dapat beroperasi dengan optimal, kontroler PID membutuhkan penalaan parameter yang tepat. Salah satu permasalahan dalam penggunaan kontroler PID adalah penentuan parameter PID yang tepat. Dalam penentuan parameter kontroler PID selama ini masih dilakukan secara konvensional, sehingga kinerja PID menjadi tidak optimal. Untuk itu pada penelitian ini akan diusulkan salah satu metode penalaan parameter PID dengan menggunakan metode cerdas berbasis Firefly Algorithm (FA), untuk mengoptimasi dan menentukan parameter yang tepat dari PID. FA adalah salah satu metode cerdas yang terinspirasi dari perilaku firefly yang bergerak dimalam hari dengan kebiasaan berkedip, yang kemudian diadaptasi dan diterapkan menjadi algoritma cerdas untuk menyelesaikan masalah optimasi. Dari hasil yang diperoleh metode Firefly dapat dengan baik menala parameter PID, sehingga overshoot yang dihasilkan tidak ada dan settling time sangat cepat. Sebagai pembanding, pada penelitian ini juga akan dibahas penggunaan metode cerdas berbasis Bee Colony dan Cuckoo Search.Kata Kunci : PID, Bee-Colony, Cuckoo, Firefly, Settling time

Design of a-based smart meters to monitor electricity usage in the household sector using hybrid particle swarm optimization - neural network Muhammad Yusuf Yunus; Marhatang Marhatang; Andareas Pangkung; Muhammad Ruswandi Djalal
International Journal of Artificial Intelligence Research Vol 3, No 2 (2019): December 2019
Publisher : STMIK Dharma Wacana

The procedure is training and testing the nerves that will be made. Matlab software has a Neural Network tool, which in this study will be used. Load sampling data is used as input data for neural network training. As output / target load classification is used. Load classification method, which is 1 for TV load classification, 2 for fan load, 3 for iron load, 4 for water pump load, 5 for lamp load, 6 for dispenser load, and 7 for fan iron load combination. The total load is 6 single loads and 1 combination load. One load combination was chosen because, on the combination load characteristics after the fan has characteristics that are not the same as the others. Data sampling of the current of each load will be used as neural network training. Load data used is 30 samples or for 30 seconds, with every minute the data is taken. From the results of the training, it can be seen that the biggest training error is in the seventh data, namely the identification of the load on the classification of the fan-iron load. This is because the current pattern on the iron and fan with the iron or fan itself has almost the same characteristics. However, for this process networks will be used and then the PSO optimization method is used to reduce the error, in the next study. From the test results, it is shown that by varying the input current data of each load, the network has been able to identify well, even though in the data classification load 7, the load of the iron-fan combination still has a large error. This will be corrected in subsequent studies with Particle Swarm Optimization (PSO) algorithm optimization.

Aplikasi Metode Cerdas untuk Optimasi Controller PID Motor DC Berbasis Firefly Algorithm Muhammad Ruswandi Djalal; Hidayatul Nurohmah; Andi Imran; Muhammad Yusuf Yunus
JURNAL NASIONAL TEKNIK ELEKTRO Vol 6, No 2: Juli 2017
Publisher : Jurusan Teknik Elektro Universitas Andalas

Controlling the speed of dc motor is very important to maintain the stability of motor operation. One of the most commonly used control methods is the proportional integral derivative (PID) controller. In order to operate optimally, PID controllers need the correct parameter tuning. One of the problems in using PID controllers is the determination of the proper PID parameters. In the determination of PID controller parameters is still done conventionally, so the performance of PID becomes not optimal. Therefore, in this research we will propose one of PID parameter tuning method by using intelligent method based on Firefly Algorithm (FA), to optimize and determine the proper parameters of PID. The FA is one of the smart methods inspired by firefly behavior that moves at night with flashing habits, which are then adapted and applied into intelligent algorithms to solve optimization problems. From the results obtained the Firefly method can well tune the PID parameters, so the resulting overshoot does not exist and settling time is very fast. As a comparison, in this study will also discuss the use of intelligent methods based on Bee Colony and Cuckoo Search.Keywords: PID, Bee-Colony, Cuckoo, Firefly, Settling timeAbstrak - Pengontrolan kecepatan motor dc merupakan hal yang sangat penting untuk menjaga stabilitas operasi motor. Salah satu metode pengontrolan yang sering digunakan adalah kontroler proportional integral derivative (PID). Agar dapat beroperasi dengan optimal, kontroler PID membutuhkan penalaan parameter yang tepat. Salah satu permasalahan dalam penggunaan kontroler PID adalah penentuan parameter PID yang tepat. Dalam penentuan parameter kontroler PID selama ini masih dilakukan secara konvensional, sehingga kinerja PID menjadi tidak optimal. Untuk itu pada penelitian ini akan diusulkan salah satu metode penalaan parameter PID dengan menggunakan metode cerdas berbasis Firefly Algorithm (FA), untuk mengoptimasi dan menentukan parameter yang tepat dari PID. FA adalah salah satu metode cerdas yang terinspirasi dari perilaku firefly yang bergerak dimalam hari dengan kebiasaan berkedip, yang kemudian diadaptasi dan diterapkan menjadi algoritma cerdas untuk menyelesaikan masalah optimasi. Dari hasil yang diperoleh metode Firefly dapat dengan baik menala parameter PID, sehingga overshoot yang dihasilkan tidak ada dan settling time sangat cepat. Sebagai pembanding, pada penelitian ini juga akan dibahas penggunaan metode cerdas berbasis Bee Colony dan Cuckoo Search.Kata Kunci : PID, Bee-Colony, Cuckoo, Firefly, Settling time

Optimal Design of Power System Stabilizer In Bakaru Power Plant Using Bat Algorithm Muhammad Ruswandi Djalal; Muhammad Yusuf Yunus; Herman Nawir; Andi Imran
JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Vol 1 No 2 (2017): October
Publisher : Muhammadiyah University, Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/jeee-u.v1i2.1017

The problem of using Power System Stabilizer (PSS) in generator excitation is how to determine optimal PSS parameter. To overcome these problems, the authors use a method of intelligent bats based algorithm to design PSS. Bat Algorithm is an algorithm that works based on bat behavior in search of food source. Correlation with this research is, food sources sought by bats represent as PSS parameters to be optimized. Bat's algorithm will work based on a specified destination function, namely Integral Time Absolute Error (ITAE). In this research will be seen the deviation of velocity and rotor angle of each generator, in case of disturbance in bakaru generator. The analysis results show that the uncontrolled system produces a large overshoot oscillation, and after the addition of PSS oscillation control equipment can be muted. So that the overshoot and settling time of each generator can be reduced and the generator can quickly go to steady state condition.

Implementasi Labview Untuk Pemantauan Pemakaian Energi Listrik Muhammad Yusuf Yunus; Marhatang Marhatang
JEEE-U (Journal of Electrical and Electronic Engineering-UMSIDA) Vol 2 No 1 (2018): April
Publisher : Muhammadiyah University, Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/jeee-u.v2i1.1321

In conventional electric measurement devices, measurements are made on the use of electrical energy as a whole where consumers can only see information on the results of the use of electrical energy by looking at the total power consumption amount indicated on the meter kWh meter. Based on the above problems, the author aims to raise the title "Design of Monitoring System of Electricity Energy Usage using LabVIEW". The LabVIEW program has the ability to measure, monitor and store data quickly and accurately. With this tool will be realized a design system monitoring the use of electrical energy in real time through the computer instead of kWH meter analog or digital. This concept is one of the energy management solutions that enable consumers to obtain statistical data on electrical energy consumption in detail. From the results of monitoring the use of loads, obtained very good results in monitoring the usage of energy, which in this case using household burden.

FLOWER POLLINATION ALGORITHM UNTUK OPTIMASI PENGENDALI PID PADA PENGENDALIAN KECEPATAN MOTOR INDUKSI Muhammad Ruswandi Djalal; Muhammad Yusuf Yunus; Andi Imran; Herlambang Setiadi
Jetri : Jurnal Ilmiah Teknik Elektro Jetri Volume 15, Nomor 1, Agustus 2017
Publisher : Website

AbstractThe use of Proportional Integral Derivative (PID) controller in induction motors is becoming more and more popular, because of its simple structure. PID controller requires proper parameter setting for optimal performance on the induction motor. The most commonly used method is by trial and error to determine parameters of the PID controller, but the results obtained are not optimal and incorrect PID controller’s parameters will damage the system. For that reason, in this research it will be shown one of PID parameters tuning method by using Flower Pollination Algorithm (FPA) to optimize and determine the exact parameters of the PID. FPA is a method that is being adapted and applied as a smart algorithm to solve optimization problem. The PID parameters tuning in this study gives results that the value of kp, ki and kd are 0.4213, 0.2337 and 0.027 respectively. As a comparison, this study has also used Firefly, Cuckoo Search, Particle Swarm, Imperialist Competitive, Ant Colony, Differential Evolution, and Bat method. The FPA method can well tune the PID parameters, so that the resulting overshoot is very small in comparison with the other methods, it is at 1,019 from the set point. Compared with other methods, the settling time is also very fast, that is 0.3second. Keywords: PID, FPA, Bee-Colony, Cuckoo, Firefly ABSTRAKPenggunaan pengendali Proportional Integral Derivative (PID) pada motor induksi menjadi semakin populer, karena strukturnya yang sederhana. Pengendali PID memerlukan pengaturan parameter yang tepat untuk kinerja optimal pada motor induksi. Metode yang paling umum digunakan adalah dengan metode trial and error untuk menentukan parameter pengendali PID, namun hasil yang didapat tidak optimal dan parameter pengendali PID yang tidak tepat akan merusak sistem. Oleh karena itu, dalam penelitian ini, diperlihatkan salah satu metode penalaan parameter PID dengan menggunakan metode Flower Pollination Algorithm (FPA) untuk mengoptimalkan dan menentukan parameter PID yang tepat. FPA adalah salah satu metode yang diadaptasi dan diterapkan sebagai algoritma cerdas untuk mengatasi masalah optimasi. Hasil penalaan yang diperoleh adalah nilai kp, k i, dan kd masing-masing sebesar 0,4213, 0,2337, dan 0,0274. Sebagai perbandingan, penelitian ini juga menggunakan metode Firefly, Cuckoo Search, Particle Swarm, Imperialist Competitive, Ant Colony, Diferential Evolution, dan metode Bat. Metode FPA dapat menala parameter PID sehingga overshoot yang dihasilkan sangat kecil dibandingkan dengan metode lainnya yaitu sebesar1,019 terhadap set point. Waktu settling yang diperoleh juga sangat cepat dibandingkan dengan metode lainnya. yaitu 0,3 detik. Kata kunci: PID, FPA, Bee-Colony, Cuckoo, Firefly

PLANNING AND FEASIBILITY STUDY OF A HYBRID SOLAR POWER PLANT WITH AN ADDED AUTOMATIC TRANSFER SWITCH (ATS) FOR AN OFFICE BUILDING Chandra Buana; Muhammad Yusuf Yunus; Muhammad Daffa Abbas; Rizal Ashari; Nita Sri Indah Sari
International Journal of Innovation in Mechanical Engineering and Advanced Materials Vol 5, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijimeam.v5i3.23244

The Office of the Regent of Sidenreng Rappang (Sidrap), situated on Harapan Baru Street, Batu Lappa, Watang Pulu District, Sidrap Regency, South Sulawesi, consumes 200 kWh of electricity daily for lighting, resulting in substantial energy costs. Recognizing the potential for renewable energy, especially with a daily solar radiation potential of 5.8 kWh/m2, this study proposes the implementation of a hybrid solar power plant system. The system incorporates Photovoltaic (PV) as the primary energy source, with the Grid and Generator serving as backup sources through an AC Coupling configuration utilizing Automatic Transfer Switch (ATS). The research employs a simulation approach using HOMER Pro software for system modeling, SketchUp software for solar panel layout, AutoCAD software for ATS circuit modeling, and theoretical calculations for financial analysis. The results indicate a solar power plant capacity of 39.6 kW, producing 75,701 kWh/year with an impressive 83.3% renewable penetration. From an economic standpoint, the project requires an investment of IDR 642,714,960, with a net present cost of IDR 1,573,177,823, and a cost of energy value of IDR 1,401.38/kWh. In terms of feasibility, the project demonstrates a net present value exceeding zero (IDR 216,680,041), a profitability index greater than one (1.33), an internal rate of return surpassing the credit interest rate (12.488%), and a payback period of 7 years and 7 months. These findings affirm the feasibility of the hybrid solar power plant planning project for the Sidrap Regent's Office, showcasing its economic viability and potential for sustainable energy solutions.

PLANNING STUDY OF HYBRID POWER PLANT SOLAR PV-DIESEL GENERATOR ON KODINGARE ISLAND, SINJAI REGENCY Muhammad Yusuf Yunus; Lewi Lewi; Andi Saiful Rijal; Nur Huda; Ahmad Ikram
International Journal of Innovation in Mechanical Engineering and Advanced Materials Vol 5, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijimeam.v5i2.23245

Kodingare Island is located in Pulau Sembilan District, Sinjai Regency, one of nine islands. Currently, most people still rely on conventional energy from diesel power plants. The reason is that this island does not yet receive an electricity supply from the electricity grid due to the geographical limitations of the archipelago. It is known that the most potential renewable energy source on Kodingare Island is solar energy, with a potential for solar radiation reaching 5.86 kWh/m2/day. This research aims to analyze an innovation that combines PV and solar, where PV acts as the main electricity generator, while solar functions as a backup and additional energy source. The method used in this research uses simulation methods, layout modeling, and financial analysis using HOMER Pro simulation software to determine the potential and performance of hybrid power plants and SketchUp Pro software to produce three-dimensional layouts and economic and feasibility values obtained through financial analysis. Technical aspects include producing an electrical energy system of 37,029 Wh/year, consisting of PV of 32,981 Wh/year and solar of 4,048 Wh/year with energy consumption of 33,850 Wh/year. The required fuel consumption is 2,086 L/year, with excess electricity of 931 kWh/year and renewable energy penetration of 89.1%. From an economic perspective, planning this hybrid power system requires an investment of 258.290.000 IDR, O&M costs of 19.350.600 IDR, and the cost of energy value of 1,352/kWh IDR. In contrast, from the feasibility aspect of planning a hybrid electric power system, it is said to be feasible because it produces a Net Present Value of 9,870,151 IDR, is more significant than zero, the Profitability Index is 1.03 greater than one, the Internal Rate of Return is 8.90% greater than the credit interest rate of 8.43% and the Payback Period required for return of capital is nine years nine months.

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