IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)
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Sistem Kendali Penerbangan Quadrotor pada Keadaan Melayang dengan Metode LQR dan Kalman Filter
Get PDFQuadrotor is a type of UAV (Unmanned Aerial Vehicle) with four propellers and four rotor. Quadrotor as flying robots has the advantage to take off and land vertically. In addition quadrotor also has the ability to fly hovered near a stationary state. However quadrotor had some difficulties to operate. One of these difficulties is to make quadrotor be able to fly and maintain the stationary state of the Euler angles (roll, pitch, and yaw). Linear Quadratic Regulator (LQR) as one of the modern control method which has the advantage of maintaining the conditions on the ground. This method can be combined with Kalman filter algorithm. It aims to reduce measurement error from the process sensor fusion and maintain Euler angles (roll, pitch and yaw).Kalman filter aims to reduce the measurement error of the sensor fusion. Then the output of Kalman filter algorithm becomes the input state for control LQR the roll angle and pitch angle. Input state is multiplied with the negative feedback as process systems. The results are converted into pulses to rotate the brushless motor so quadrotor can fly stably.The test results showed quadrotor while maintaining stability against roll angle has overshoot of 0.35 ° and the pitch angle has overshoot of 2 °
Rancang Bangun Spectrum Analyzer Menggunakan Fast Fouier Transform Pada Single Board Computer
Get PDFSpectrum analyzer is an instrument device to measure the magnitude of the frequency and the power of signal. It has many benefits, such as used for testing telecommunication devices, determining the allocation of unused frequencies and also for practicum in schools or universities. However, because of these many benefits, the price of this signal measuring equipment soared in the market.As an alternative, a device that can serve as spectrum analyzer yet has an affordable price is invented in the form of the prototype of spectrum analyzer built using a single board computer by applying a fast Fourier transform algorithm. Feedback from the prototype is in the form of radio signal captured using RTL-SDR.The test results showed that the range of frequencies that can be displayed by the prototype is 24 MHz to 1.769 MHz. Then the test results of fast Fourier transform computing on N points showed that the prototype can work smoothly using the N from 512 to 32.768 points. The use of N more than 32.768 points will cause CPU and disk memory overloaded and lead to a slow performance. Finally, comparison of the levels of spectrum was performed using spectrum analyzer Anritsu MS2720T. As a result, it is known that prototype can be used to show the location of the frequency spectrum of the radio signal appropriately
Purwarupa Sistem Pembuka Pintu Cerdas Menggunakan Perceptron Berdasarkan Prediksi Kedatangan Pemilik
Get PDFArrival prediction system on smarthome is system that cam estimating time of home owner arrival on smarthome. Prediction system used to reference on smarthome system to preparing electronic devices so at home owner arrive, the devices are already to use. Prediction system made by divide distance of home owner location to home by driving velocity. Prediction also use neural network perceptron to determine travel condition are in traffic or not and correcting to predicting perform. Perceptron use last travel data as reference correction to prediction system. Based on testing on prediction system, accuracy of prediction system reach 74% to 79%. Accuracy reach these values due errors occurred while determining location so predicted route became not match with real condition. Errors occured by GPS usage not on outdoor area and smartphone GPS only detect 6 GPS satellite. Neural network perceptron differ of traffic condition on travel after fourth epoch, with weight value at 11.09 and bias value at 61. And perceptron can correcting prediction system after twelfth epoch with weight values at -0.2778 and 0.2924 also bias value at -0.05
Sistem Pentautan Citra Udara Menggunakan Algoritme SURF dan Metode Reduksi Data
Get PDFOne of the algorithm for aerial image stitching system is SURF (Speeded Up Robust Features). It is a robust algorithm which is invariant to image scale, rotation, blurring, illumination, and affine transformation. Although SURF has good performance, some of the detected keypoints are not always considered as necessary keypoints . As a result, these unnecessary keypoints are needed to be eliminated to decrease computation time.The proposed system uses SURF detector in the detection process. The data reduction method will eliminate couple of keypoints which have near distance each other. Next, the keypoints will be described by SURF descriptor.The description Results further matched using FLANN. The next step is the search pattern with RANSAC homography matrix and stitch the picture to accumulate keypoints using warpPerpective.Stitching system are tested with some variations, such as scale variations, rotation variations, and overlap variations on the image. Based on the result, the proposed Data Reduction method has optimum value of minimal radius from 40 pixels to 100 pixels. The stitching process is still working with up to 90% keypoint number reduction. Average computation time using data reduction method are 39,41% faster than without data reduction method
Sistem Kendali Gimbal 2-Sumbu Sebagai Tempat Kamera Pada Quadrotor Menggunakan PID Fuzzy
Get PDFThe function of camera gimbal control system that use in this research is to serves with the angle changes that occur due quadrotor maneuver. The PID control with tuning classical method has weakness, which is the PID variable not independently adjust to the environment, thus proposed using PID fuzzy control.Gimbal camera used in this study has a mechanical design with two joint (pitch and roll) and the BLDC motor as actuator. The angle changes that occur in the pitch and roll axis will be a feedback system. Then, fuzzy logic will tune the PID variable based on that feedback.Results of testing the system on 2-axis gimbal camera shows the PID fuzzy control generates better response in parameter risetime, overshoot, and settlingtime compared with PID control. Error input value range of [-30° 30°] and delta error of [-10° 10°] on the pitch and roll axes. The range of the output value for the pitch axis is, Kp at [40.2 46.2], Ki at [10.7 20.7], and Kd of [0.05 to 0.15]. The range of the output value for the roll axis is, Kp at [6.4 16.4], Ki at [17.3 to 27.3], and Kd at [0.08 0.16]. Speed response speed of pitch axis is 0.12 second and the roll axis is 1.07 seconds
Sistem Kendali Penghindar Rintangan Pada Quadrotor Menggunakan Konsep Linear Quadratic
Get PDFQuadrotor is one of UAV (Unmanned Aerial Vehicle) rotary wing aircraft type. Quadrotor has been widely used for various needs to military or civilian. Quadrotor can be operated manually by remote or autonomously. One of the difficulties of quadrotor operations is to avoid the obstacles before autonomous flying towards destination point. Therefore, an obstacle avoidance control system is required on quadrotor systems. Linear Quadratic Regulator is a control system that produces an input value system from state value and feedback. State value is produced from translation and rotation. That input value then converted into pulse width modulation to control the speed of the brusless motor, and it's used to do obstacles avoidance manouver.This method might reduce overshoot on the system and make response time (rise time) arrived faster than other methods. The obstacle avoidance system requires small overshoot value and an appropriate response time to avoid frictions or collisions. The result of this research is the rise time to avoid obstacles that reached 4,7 second with flight speed of 0,6 m/s and turns for roll angle equal to 14,27 °, pitch equal to 13,26 °, and yaw equal to 9,87 ° while avoidance maneuvering obstacles
Pengaruh Latar Belakang Warna pada Objek Gambar terhadap Hasil Ekstraksi Sinyal EEG
Get PDFIn this study, observation on the differences in features quality of EEG records as a result of training on subjects has been made. The features of EEG records were extracted using two different methods, the root mean square which is acquired from the range between 0.5 and 5 seconds and the average of power spectrum estimation from the frequency range between 20 and 40Hz. All of the data consists of a 4-channel recording and produce good quality classification on artificial neural network, with each of which generates training data accuracy over 90%. However, different results are occured when the trained system is tested on other test data. The test results show that the two systems which are trained using training data with object with color background produce higher accuracy than the other two systems which are trained using training data with object without background color, 63.98% and 60.22% compared to 59.68% and 56.45% accuracy respectively. From the use of the features on the artificial neural network classification system, it can be concluded that the training system using EEG data records derived from the visualization of object with color background produces better features than the visualization of object without color background
Klasifikasi Sel Darah Putih Menggunakan Metode Support Vector Machine (SVM) Berbasis Pengolahan Citra Digital
Get PDFWhite blood cells are classified into five types (basophils, eosinophils, neutrophils, lymphocytes and monocytes) with additional classes lymphoblast cells from microscope images are processed. By applying image processing, image its white blood cells extracted using the Histogram Oriented Gradient. Feature extraction results obtained then classified using Support Vector Machine method by comparing the results of two different kernel parameters: kernel Linear and kernel Radial Basis Function (RBF). Classification evaluated with these parameters: Accuracy, specificity, and sensitivity.Obtained an accuracy of 72.26% from the detection of white blood cells in the microscope image. The average value of microscope images of patients and different kernel every white blood cells (monocytes, basophils, neutrophils, eosinophils, lymphocytes and lymphoblast) were evaluated with these parameters. Results of the study show the classification system has an average value of 82.20% accuracy (RBF Patient 1), 81.63% (RBF Patient 2) and 78.73% (Linear Patient 1), 79.55% (Linear Patient 2 ), then the value of specificity of 89.91% (RBF patient 1), 92.18% (RBF patient 2) and 88.06% (Linear patient 1), 91.34% (Linear patient 2), and sensitivity values 15 , 45% (RBF patient 1), 12.97% (RBF patient 2) and 13.33% (Linear patient 1), 12.50% (Linear patient 2)
Pendeteksian Bola untuk Robot Sepak Bola Humanoid Berbasis Pengenalan Pola
Get PDF Humanoid soccer robot is one of popular developed robot. RoboCup is a competitive competiton of humanoid robot soccer. The rule of RoboCup changed by the time, the previous orange ball changed by white ball which is same color as the field line and the goal. Accordingly, in this research designed a white ball detection system for humanoid soccer robot based on pattern recognition. Histogram of Oriented Gradient (HOG) and Support Vector Machine (SVM) method are used in this research for feature extraction and classification. The result of this research is a system that be able to detect ball in humanoid soccer robot environment. The system tested by sliding window parameter testing, the distance of ball to robot testing, different light intensity testing, and other object testing. The conclusions of this research are: optimal detection is obtained by using 8x8 win_stride parameter size and 1,2 scale0 parameter value, maximum distance of detection with 32×32 window detector is 180 cm and with 64×64 window detector is 140 cm, the response of system in different light intensity is good enough, and the success rate of system against other obstacle object with 32×32 window detector is 68% and with 64×64 window detector is 99%
Pengendalian Kestabilan Ketinggian pada Penerbangan Quadrotor dengan Metode PID Fuzzy
Get PDF Quadrotor is a kind of unmanned aerial vehicle that have the ability to take of vertically and maintaining its position while flying mid-air. Flying a quadrotor sometimes needs a stable altitude to perform a specific mission. A stable altitude will make easier for pilot to control the movement of the quadrotor to certain direction.This study designed and implemented a system that can stabilises the altitude of a quadrotor by using Fuzzy-PID method. Altitude control system needed to help pilot controls the altitude stability without adjusting the throttle. Control with PID method is a common control system to be implemented on a quadrotor. This control system has a constant that can be tuned with fuzzy logic with linguistic approach to improve the response time when compensating an error. The result of this study shows that Fuzzy PID control method generate a better response time compared with the PID-only method. The implementation of PID control generate an altitude stabilisation with a mean value steady state error of ±1,86 cm, whereas the PID Fuzzy generate a mean value of steady state error of ±1,22 cm