ABSTRAKSimulator penggunaan energi listrik sangat membantu dalam perencanaan pasokan listrik secara terus menerus atau perlu pemadaman bila terjadi gangguan. Agar kinerja pembangkit dapat kembali normal, bertahap, dan terencana akibat mengalami gangguan, maka digunakan metoda Load Shedding. Sistem otomasi dibutuhkan untuk merealisasikan metoda Load Shedding, dan melalui simulator dapat mengurangi resiko terhadap kerusakan bila langsung diimplementasikan. PLC digunakan untuk memprediksi beban saat load shedding, sedangkan SCADA digunakan untuk menampilkan prioritas dan status beban. Load shedding 1 adalah tindakan pelepasan beban bila pada salah satu genset mengalami gangguan, sedangkan Load shedding 2 bila pada kedua genset mengalami gangguan. Simulasi sistem load shedding 1 dan 2 berhasil dilakukan pelepasan beban secara otomatis. Setelah pelepasan beban, kapasitas beban yang ditanggung genset sesuai dengan prediksi dari PLC. Terdapat perbedaan hasil antara daya yang diprediksi secara perhitungan dan daya terukur, kemungkinan disebabkan beban masih belum steady saat data diambil.Kata kunci: Otomasi, Simulator, Sistem Load shedding, SCADA, PLC ABSTRACTSimulator of the use of electrical energy is very helpful in planning electricity supply continuously or needs to be suppressed if a disturbance occurs. In order for the generator performance to return to normal, gradual, and planned due to interference, the Load Shedding method is used. Automation systems are needed to realize the Load Shedding method, and through simulators can reduce the risk of damage if implemented immediately. PLC was used to predict load during load shedding, while SCADA was used to display priority and load status. Load shedding 1 was a load release action if one of the generator sets was disrupted, while Load shedding 2 if in both gensets were disrupted. Load system simulation of shedding 1 and 2 was successfully released by load automatically. After the load was released, the load capacity borne by the generator was in accordance with the predictions of the PLC., the load capacity borne by the generator was in accordance with the predictions of the PLC. There was a difference in results between the predicted power and measured power, possibly because the load was stillnot steady when the data was taken. Keywords: Automation, Simulator, Load Shedding System, SCADA, PLC
ABSTRAKPenggunaan dan aplikasi motor Brushless DC cukup banyak di industri, namun masih cukup sulit untuk mengendalikannya. Pada penelitian sebelumnya telah dipelajari karakteristik parameter motor BLDC UAV menggunakan Metode Regresi untuk mengetahui hubungan antar parameter yang ada dalam sistem motor BLDC. Sinyal PWM merupakan salah satu yang menentukan kecepatan rotor dari BLDC. Pada penelitian ini identifikasi model motor BLDC hasil eksperimen digunakan untuk mengendalikan kecepatan rotor secara open loop dan closed loop. Pengendalian secara open loop menggunakan invers model hasil Metode Regresi menghasilkan kesalahan maksimal 3,77% untuk kecepatan rotor lebih dari 3500 rpm. Sedangkan pada pengendalian secara closed loop menggunakan model hasil Metode Regresi dan pengendali PI (Proportional Integral) dengan Kp = 1 dan Ki = 5, secara simulasi menghasilkan kecepatan rotor dengan settling time 1 detik.Kata kunci: motor BLDC, kecepatan rotor, identifikasi model, pengendalian ABSTRACTThe use and application of Brushless DC motors is quite a lot in the industry, but it is still quite difficult to control. In previous research the characteristics of UAV BLDC motor parameters using the regression method to determine the relation of the parameters in the BLDC motor system. The PWM signal is one that determines the rotor speed of the BLDC. In this study the identification of the BLDC motor model experimental results is used to control the rotor speed in open loop and closed loop. Control with open loop using the inverse model of the Regression Method produces a maximum error of 3.77% for rotor speeds of more than 3500 rpm. Whereas control with closed loop using the model of the Regression Method and PI (Proportional Integral) controller with Kp = 1 and Ki = 5, the simulation produces rotor speed with a settling time of 1 second.Keywords: BLDC motor, rotor speed, model identification, control
ABSTRAKSistem pick and place merupakan suatu sistem mekanik yang digunakan untuk memanipulasi pergerakan mengangkat, memindahkan, dan meletakkan untuk meringankan kerja manusia. Dalam mempelajari cara kerja robot industri sederhana dibuat miniatur robot pick and place (sederhana). Perancangan yang dibuat yaitu sistem pick and place dengan dua derajat kebebasan dengan ukuran yang memiliki perbandingan 1:0.35 dari referensi ukuran desain robot. Aplikasi SolidWorks digunakan untuk mendesain robot Diamond. Metode Regresi digunakan untuk memprediksi posisi motor servo dalam mencapai posisi yang diinginkan. Metode regresi berhasil digunakan untuk mencari hubungan antara target posisi setpoint dengan posisi motor servo 1 dan 2 (persamaan orde 2 dan 3) untuk mengontrol motor servo. Performansi yang terbaik dari sistem pick and place yang dibuat menggunakan trayektori miring, dengan kecepatan 100 (11.1 rpm), menghasilkan error ± 0.0729 dan presisi 1.63%. Dalam penelitian ini, kecepatan end-effector yang lebih rendah menghasilkan keakurasian dan kepresisian yang lebih baik.Kata kunci: Pick and Place, Robot Diamond, Dua derajat kebebasan, Regresi ABSTRACTThe pick and place system are a mechanic system used in manipulating the movements of lifting, moving, and laying to ease human work. In learning how to work a simple industrial robot, a miniature pick and place robot is created. The design made is a pick and place system with two degrees of freedom with a size that has a ratio of 1: 0.35 from the reference size of the robot design. Regression method is used to predict the position of the servo motor in reaching the desired position. Regression method was successfully used to find the relationship between the target setpoint position and the position of servo motors 1 and 2 (order equations 2 and 3) to control the servo motor. The best performance from the pick and place system that is made using an aslope trajectory, with a speed of 100 (11.1 rpm), produces an error ± 0.0729 and precision 1.63%. In this research, lower end-effector speeds result in better accuracy and precision.Keywords: Pick and Place, Diamond Robot, 2-DOF, Regression
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