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Journal of Robotics and Control (JRC)
Published by Universitas Muhammadiyah Yogyakarta
ISSN : 27155056     EISSN : 27155072     DOI : https://doi.org/10.18196/jrc
Core Subject : Science, Engineering,
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering
Journal of Robotics and Control (JRC) is an international open-access journal published by Universitas Muhammadiyah Yogyakarta. The journal invites students, researchers, and engineers to contribute to the development of theoretical and practice-oriented theories of Robotics and Control. Its scope includes (but not limited) to the following: Manipulator Robot, Mobile Robot, Flying Robot, Autonomous Robot, Automation Control, Programmable Logic Controller (PLC), SCADA, DCS, Wonderware, Industrial Robot, Robot Controller, Classical Control, Modern Control, Feedback Control, PID Controller, Fuzzy Logic Controller, State Feedback Controller, Neural Network Control, Linear Control, Optimal Control, Nonlinear Control, Robust Control, Adaptive Control, Geometry Control, Visual Control, Tracking Control, Artificial Intelligence, Power Electronic Control System, Grid Control, DC-DC Converter Control, Embedded Intelligence, Network Control System, Automatic Control and etc.
Arjuna Subject : Teknik (semua kategori) - Teknik Kontrol dan Sistem
Articles 708 Documents
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Validation Method for Digital Flow Meter for Fuel Vendors Prisma Megantoro; Danar Aulia Husnan; Mian Usman Sattar; Andino Maseleno; Omar Tanane
Journal of Robotics and Control (JRC) Vol 1, No 2 (2020): March
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.1210

Abstract

Research on the design of fuel measuring device for vendors using Arduino Mega 2560 microcontroller and positive displacement flow meter sensor was conducted. It aimed to design and create a prototype of fuel measuring device for retail traders, and to find error values on the device. The research began with searching for reference books, making hardware and programming, and finally testing the device. The components used were Arduino Mega 2560, positive displacement flow meter sensor, keypad, selenoid valve and 4x20 LCD. The test was performed by comparing the results of the measuring cup to the number displayed on the LCD, followed by reproducibility. Data collection was carried out every volume of 500ml, 1000ml, 1500ml, and 2000ml. The results of the research showed that the error value was 2.24% with the comparison of 1.91%. Several factors affecting the highness of error value were human factor, sensor and device factor, as well as the comparison device being used. Referring to the error value that smaller than 5%, this device is worthy for mass production
Simulation of Vetilligo Therapy Equipment Nur Hudha Wijaya; Adelia Agtesa; Gabriel De Brito Silva; V. Dhinakaran; Mian Usman
Journal of Robotics and Control (JRC) Vol 1, No 4 (2020): July
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.1426

Abstract

Vitiligo is a skin disorder caused by a lack of melanin pigment in the skin, which causes white patches on certain parts of the skin because this melanin pigment is not able to produce the skin color. Previously, one of the treatments for vitiligo was using a UVB lamp with a 311 nm wavelength that could not yet be adjusted to dim the lights as safety when conducting therapy. Therefore, the research aims to design a simulation of the vitiligo therapy device equipped with a timer LED lamp, a safety of lighting, and the data storage. The data are stored in the SD Card to make it easier for patients to control changes before and after therapy. The simulation of this therapeutic apparatus is controlled using the Arduino Uno system and regulates lightning protection using a PWM circuit and ultrasonic sensors. The highest error obtained is 2.4%. at 5 cm. The overall device system, namely timer, buzzer, hour meter, and data storage has been working well and the error value is still within tolerance which is below 5%. Thus, it is hoped that this vitiligo therapy simulation device is able to operate as a real therapeutic device
Induction Motor DTC Performance Improvement by Reducing Flux and Torque Ripples in Low Speed Yassine Zahraoui; Mohamed Akherraz; Chaymae Fahassa; Sara Elbadaoui
Journal of Robotics and Control (JRC) Vol 3, No 1 (2022): January
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i1.12550

Abstract

Since induction motors were invented, human civilization has changed forever. Due to their beneficial characteristics, induction motors are widely used and have become the most prevalent electrical counterparts. Many control strategies for induction motors have been developed, varying from scalar to vector control. In the class of vector control, the Direct Torque Control (DTC) was proposed as an alternative that ensures separated flux and torque control while remaining completely in a stationary reference frame. It offers direct inverter switching, reasonable simplicity than other vector control techniques, and less sensitivity to parameter variation. However, the use of hysteresis controllers in conventional DTC involves non-desired ripples in the system's flux and torque, which leads to bad system performances, primarily in low-speed operations. This paper aims to minimize the chattering and ensure the augmented system's performance in terms of robustness and stability. The proposed method is an improved version of DTC, which combines the addition of the Space Vector Machine (SVM) algorithm to the DTC and the increased number of DTC sectors that generate reference control voltages. Satisfactory results have been obtained by numerical simulation in MATLAB/Simulink. Eventually, the proposed method is proven to be a fast dynamic decoupled control that robustly responds to external disturbance and system uncertainties, especially in the low-speed range.
Forecasting of The Number of Schizophrenia Disorder by using The Box-Jenkins of Time Series Analysis Syifa Putri Humaira; Indah Nursuprianah; Darwan Darwan
Journal of Robotics and Control (JRC) Vol 1, No 6 (2020): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.1640

Abstract

Schizophrenia is a mental disorder with a complex brain disorder that causes sufferers not to be able to distinguish between reality and imagination. This study aims to determine the parameters for the best model Box-Jenkins time series analysis in predicting the number of schizophrenic in Cirebon City in 2018 as seen from the smallest MSE (Mean Square Error) value. This study uses Box Jenkins method (often referred to as the ARIMA Method) with documentation collection techniques and literature studies. The documentation aims to collect data on the number of schizophrenic patients in January 2014 to December 2018. Data were analyzed in several stages, namely the stage of data stationary identification, determining model parameter estimates, model verification and forecasting. The results of this study show that the best model for predicting the number of schizophrenic patients in the future is ARIMA (0,1,1). The forecasting results of the number of schizophrenic patients in Cirebon City from January to December 2018 respectively are 69 people, 68 people, 68 people, 68 people, 68 people, 68 people, 67 people, 67 people, 67 people, 67 people, 67 people, 67 people.
Nebulizer Operational Time Control Based on Drug Volume and Droplet Size Using Fuzzy Sugeno Method Ibnu Rizal Fadhlurahman Arif; Ahmad Firdausi; Galang P. N. Hakim
Journal of Robotics and Control (JRC) Vol 2, No 2 (2021): March
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.2259

Abstract

Nebulizer is one of the electro medic devices that serve to provide therapy for patients who experience abnormalities or disorders of the respiratory tract. Nebulizer system works using piezo electronic device to produces high frequency vibration. With this high frequency vibration the drug liquid molecules breaks down become fumes, thus it can easily to inhale for patient even for children. Unfortunately like other aerosol drug delivery system, the operation of nebulizer is also still manual. The patient doesn’t really know when the drug is empty on the canister. The nurses also need to check in regularly to see if the drugs are empty or not. In this paper a fuzzy sugeno methods is used to give prediction of nebulizer time operational. We propose fuzzy sugeno to calculate the time operational nebulizer using two parameters, such as drug droplet size and drug liquid volumes that have been administer by nurses. Using fuzzy sugeno method we can solve the nebulizer manual operational time problem. Our result show that the longest operational time was 26.07 minutes, this achieve when liquid volume was 5 ml and the size of drug droplet was 1 um. Meanwhile for the shortest operational time was 8.07 minutes, this achieve when liquid volume was 10 ml and the size of drug droplet was 4 um. We can conclude that we had successful to control nebulizer operational time using fuzzy sugeno method.
Automatic Wireless Nurse Caller Sigit Widadi; Sultan Al Badrun Munir; Nishith Shahu; Irfan Ahmad; Israa Al Barazanchi
Journal of Robotics and Control (JRC) Vol 2, No 5 (2021): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.25111

Abstract

The nurse caller device is used as a special communication device between the patient and the nurse within the hospital area as a means of speeding the nurse's time response in providing immediate care to the patient. The designed wireless-based nurse caller device made installation easier and neater. The remote used a Bluetooth module MH-10 connected to the ATMega8 microcontroller as the sender and receiver. The data process using a microcontroller ATMega8 produced characters on the LCD, turned on the LED, and activated the buzzer to call the nurse. The results of the test on the device showed that the farthest distance taken by the HM-10 Bluetooth module in the open area (outdoor) was about 45 meters, and the closed area (indoor) was about 20 meters.
Web-Based Flood Hazard Monitoring Anna Nur Nazilah Chamim; Dwi Cahyo Hardyanto; Karisma Trinanda Putra
Journal of Robotics and Control (JRC) Vol 2, No 5 (2021): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.25110

Abstract

Flood is a natural disaster. It occurs in several cities in Indonesia. Floods caused by rivers that overflowed and then flooded residential areas. It comes mostly unexpectedly without early warning. It causes many losses, especially the loss of material, and health threats to surrounding communities. The advance of network technology can reduce the adverse effects of flooding by providing warning alarms and water level monitoring system in real-time that can be accessed via the web. Based on the problem, a monitoring system was designed to monitor water levels via a web that work in real time for 24 hours, and store water level data into the database. The use of this website requires an internet connection, so that internet services must be available.
Light Control Using Human Body Temperature Based on Arduino Uno and PIR (Passive Infrared Receiver) Sensor Reza Perkasa; Refni Wahyuni; Rika Melyanti; Herianto -; Yuda Irawan
Journal of Robotics and Control (JRC) Vol 2, No 4 (2021): July
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.2497

Abstract

This study aims to implement the PIR sensor, Arduino UNO and 2 channel relay Module to automatically turn on the lights in the classroom at the STMIK Hang Tuah Pekanbaru campus, where the classes at the Hang Tuah Pekanbaru STMIK campus still use manual switches as controllers lights on. Therefore, a device is designed that can control the lights by using movements detected by the PIR sensor and processed using a computer.This system functions to turn on the lights automatically when someone enters the classroom and turn off the lights automatically when no one is in the class. The hardware used is Arduino Uno microcontroller, PIR motion sensor, 2 channel relay module, and 1.5 volt flashlight. The software for making programs is Arduino IDE where the programming language used is the C programming language. The test results show that the PIR sensor can detect the movement of people entering or leaving a room.
Autotuning Fuzzy PID Controller for Speed Control of BLDC Motor Roedy Kristiyono; Wiyono Wiyono
Journal of Robotics and Control (JRC) Vol 2, No 5 (2021): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.25114

Abstract

The PID control system is widely used for industrial machine control processes. The success of PID control is determined by tuning PID parameters. In PID control the tuning is carried out offline without taking into account changes that occur in the plant and the disturbances that arise. This study aims to optimize PID parameters online by taking into account the changes that occur in the plant and the disturbances that arise using fuzzy logic-based controls and tested on a BLDC motor which is a non-linear system. Set PID parameters with fuzzy logic using a combination of 49 if-then rules. To set proper PID parameters in real time, a two-level control system was built. The first level to define PID parameters by finding the minimum and maximum values of  kp, ki and kd by the reaction method curve. The second level is designing the Fuzzy system to automatically set the PID parameters, then formulating a combination of 49 fuzzy if-then rules to get the value kp, ki, kd, error and change in delta error value. Testing of set point changes at BLDC Motor loads with no load and 0.5kg load and changes in speed get a response from the PID control system with an average value of 0.025 seconds rise time, 0.1625 seconds preset time, and 15.98% overshoot. While the Fuzzy PID control produces an average rise time value of 0.0025 seconds, preset time 0.057 seconds, overshoot of 5.42%.
Design and Implementation of Artificial Neural Networks to Predict Wind Directions on Controlling Yaw of Wind Turbine Prototype Zaky Dzulfikri; Nuryanti Nuryanti; Yuliadi Erdani
Journal of Robotics and Control (JRC) Vol 1, No 1 (2020): January
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.1105

Abstract

Wind  energy as one of the new renewable energies has an important role in replacing fossil energy sources in Indonesia. In order to make the wind turbine's performance more efficient in extracting energy from the wind, it is necessary to control the actuation movements pitch and yaw of the wind turbine horizontal. Controlling the actuator yaw can increase the absorption efficiency of the power to the rotor face toward the direction of the wind. The purpose of this thesis is to be able to predict the direction of the coming wind, then move the turbine rotor in the predicted direction. In this final project a wind turbine prototype is used with a precision of 5.3%, then for the data acquisition section, a wind direction sensor is built to change the amount of wind direction to a quantity that can be measured in units of degrees, and anemometer to measure wind speed. In making the wind direction prediction algorithm, artificial neural network (ANN) method is used with input parameters such as wind speed, temperature, humidity, pressure, and altitude. Data acquisition is done at one minute intervals with long data collection for one day, 1072 data are obtained, the data is then fed to the ANN model that has been prepared. Based on the results of tests that have been done, it is found that the Mean Absolute Error in the model is 0.4%.

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