Pemodelan dan Simulasi Robot Lengan 3 DOF Menggunakan V-REP

Movement of objects from one position to another position is usually by conventional method of human strength. Development of robotics technology makes movement of objects in the industry by arm robot system. By using arm robot system, the work more effective. The aim of this reaserch is to modeling 3 Degree of Freedom arm robot with kinematics method using V-REP software. Kinematics method is a subject that analyze robot movement without knowing the force that causes the movement. This research use the forward kinematics method so that arm robot can reach the goals. The input from this robot is an angle which is computed using the forward kinematics method. The output is an end-effector coordinate. Based on the result of the research, the 3 Degree of Freedom arm robot is capable to move the object from one position to another position and an error that occurs can achieve 4,99% for x coordinate, 5,57% for y coordinate, and 3,18% for z coordinate. Based on these results, the 3 Degree of Freedom arm robot with the forward kinematics method can be simulated in V-REP software effectively

Pengaruh Penggunaan Perturb & Observe pada MPPT terhadap Daya Keluaran Sel Surya

Optimizing the solar cell output power requires a tracker. The tracker which produce a maximum output power is called a maximum power point tracking (MPPT). In this research, each component in MPPT is modeled into Simulink. By using a perturb and observe (P & O) algorithms, this simulation is designed to optimize the solar cell output power. The output of the algorithm is a duty cycle. This parameter is fed into a buck-boost converter to convert the solar cell output voltage to the output voltage. The simulation results show that MPPT can increase the output power up to 37.82% dispite of the sun irradiation, temperature and load changes

Sistem Navigasi Quadrotor Berbasis IMU dengan Kalman Filter Tuning

The navigation system on quadrotor is important to maintain stability and determine its own position when flying autonomously. The GPS can provide the position measurement, but it has limitations in the specific environments and cannot provide the orientation information. This study aims to design the navigation system for quadrotor based on IMU sensor with Kalman filters using the state space model. The system model was developed using Matlab software. Kalman filter is designed to estimate the navigation data and eliminate noise on the sensor so that it can improve the measurement accuracy. The test results showed that the system model can provide orientation estimation and translation estimation of the quadrotor, while the Kalman filter model is acceptable to reduce noise on the sensor's raw data. When tested indoors, the system can provide the measurement accuracy above 90%

Rancang Bangun Receiver Menggunakan Antena 1090 MHz dan Low Noise Amplifier untuk Menambah Jarak Jangkau Penerimaan Sinyal dan Data Parameter Target ADS-B Berbasis RTL820T2

Radar technology at several airports is still using flightradar24 as a source of information, and building an ADS-B station is expensive. However, the flightradar24 has several weaknesses, among which is that if the user wants to display more information, the user is required to pay periodically or subscriptions, and there is delay due to the process of data that requires the Internet connection. With a concept of receiver ads-b based RTL-SDR R820T2, a low cost receiver ads-b with the results can receive an ads-b signal without delay and can receive data from an airplane. But there is a weakness in rtl-b receivers based RTL-SDR R820T2, because it doesn't explain and can't know how far the receiver can receive signals and target parameters data from the aircraft. Thus on this research a receiver ads-b using RTL-SDR R820T2, with a low-noise amplification and an ads-b antenna 1090 MHZ in the hopes of knowing how far the aircraft's target range is from the receiver and knowing how far the receiver's range of data signals the target parameters. By performing some step-by-step testing of the design. The designed receiver ads-b USES low noise amplification with an ads-b antenna 1090 MHZ capable of receiving data and target parameters ads-b for 284 km on adsbSCOP software range and 287.63 km mathematically

Kalman Filter untuk Mengurangi Derau Sensor Accelerometer pada IMU Guna Estimasi Jarak

This study aims to develop a Kalman filter algorithm in order to reduce the accelerometer sensor noise as effectively as possible. The accelerometer sensor is one part of the Inertial Measurement Unit (IMU) used to find the displacement distance of an object. The method used is modeling the system to model the accelerometer system to form mathematical equations. Then the state space method is used to change the system modeling to the form of matrix operations so that the process of the data calculating to the Kalman Filter algorithm is not too difficult. It also uses the threshold algorithm to detect the sensor's condition at rest. The present study had good results, which of the four experiments obtained with an average accuracy of 93%. The threshold algorithm successfully reduces measurement errors when the sensor is at rest or static so that the measurement results more accurate. The developed algorithm can also detect the sensor to move forward or backward

Sistem Pengendali On-Off Lampu dan Motor Servo sebagai Penggerak Gerendel Pintu Berbasis Internet Of Things (IoT)

The application of Internet of Things (IoT) technology will be one of the technologies that complements all fields along with the increasing use of smartphones. The purpose of this research is to design an on-off control system for lights and servo motors as door latch actuator based on IoT. The designed system can give commands on/off the lamp or door latch actuator and display the on/off indicators through an application on an Android smartphone. The system is designed using a Wemos D1 mini microcontroller as a processor, light sensor, infrared sensor, relay, servo motor, and RemoteXY app. Based on the test results, the system design has been successfully implemented and can be operated as an on-off controller via the internet with an Android smartphone. For each test performed, the system managed to provide an output that matches the given control input. The response time (delay) of the relay when on or off the lamp about 34,83 ms while the response time of the servo motor when opening and closing the latch takes about 38,93 ms. The notification shown corresponds to the state of the lamp and the state of the latch

Pengembangan Sistem Pemantau Kebocoran Gas Elpiji dan Peringatan Dini Bahaya Kebakaran Berbasis Internet Of Things

The fire hazard due to an LPG cylinder explosion can be triggered from a gas cylinder leak. Not infrequently these incidents lead to loss of life and property loss. This study proposes the design of an LPG gas leak monitoring system and early warning of fire hazards. The system is designed to be integrated with the internet network through the Internet of Things (IoT) platform. The MQ-6 sensor module is used to detect LPG gas leaks and a fire sensor to detect fire. The sensor is installed close to the gas outlet source to ensure gas leakage and fire. The data from the sensor is read by the microprocessor and sent to the web server via the interface device. When the concentration of LPG gas in the air exceeds a certain level or a fire is detected, the microprocessor gives a command to turn on the alarm and sends a hazard notification to the smartphone. Hazard notifications, gas concentrations and status of hazard conditions can be accessed in real-time on Android-based smartphones. The results of the tests that have been carried out show that this system can provide information on hazard notification messages and gas concentration values in the range of 1000 - 10000 ppm. The fire detector in this system can detect fires up to a distance of 110 cm from the source of the fire. Then, hazard notifications and gas concentration levels can be accessed via a smartphone with the Kodular web application in the form of a real-time graphic display

Penentuan Orientasi dan Translasi Gerakan UAV Menggunakan Data Fusion Berbasis Kalman Filter

Navigation system is essential in estimating the orientation and translation motion of UAV. The system can utilize data from several sensors and devices, e.g. MIMU and GPS. The orientation of UAV can be precisely calculated by means of data from accelerometer and magnetometer when both sensors are in static state. Meanwhile, under dynamic conditions, the orientation can be more precisely predicted through the use of gyroscope sensor data. In order to attain a robust navigation system, a data fusion based on Kalman filter is built to estimate the orientation from the accelerometer, gyroscope, and magnetometer sensors. Moreover, for sake of achieving high accuracy, the filter will further correct the orientation by giving a higher weight to the data from accelerometer and magnetometer sensors when the UAV is in static condition. In the case of its position, the UAV position will be estimated by performing data fusion of MIMU and GPS data. Based on the experiments, it could be showed that data fusion based on Kalman filter provided more accurate results of orientation and position of UAV. The result of orientation based on gyroscope sensor data has an average error of 18.12°, while those obtained by accelerometer and magnetometer sensors data is 1.3°. Furthermore, by using the data fusion based on Kalman filter, the error of orientation predicted by combining data from accelerometer, magnetometer, and gyroscope will decrease to 0.87°