scholarly journals Penerapan Metode Fuzzy Sugeno Sebagai Sistem Navigasi Robot Menggunakan Mikrokontroler Arduino dan Sensor Ultrasonik

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Husnawati Husnawati
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Good Control ◽  
Ultrasonic Sensor ◽  
Human Needs ◽  
Fuzzy Logic Method ◽  
Arduino Uno ◽  
Work Done ◽  
Robot Path ◽  
Logic Method

<p align="center"><strong><em>Abstract <br /></em></strong></p><p><em>In the era of industrial technology and automation, robots are widely used as a tool that can ease human work, so the robot which has a good control system is needed so that the work done by the robot can be optimized. The development of control systems in robots is currently quite rapid along with increasingly diverse human needs. Several methods are applied to the robot control system automatically. Fuzzy logic is a method that is most used in navigating robot motion. In this study will be applied Sugeno type fuzzy logic method as a robot navigation system which embedded in Arduino Uno microcontroller and ultrasonic sensor is used as distance input value, in each robot path is given 30 cm obstacle so that the PWM value generated by the robot can be measured. The results obtained in this study is the Sugeno fuzzy logic method which embedded in the Arduino Uno microcontroller can control the motion of the robot and avoid the obstacles in the environment well.</em></p><p><strong><em>Keywords</em></strong><em>:</em><em> Control System, Navigation, Fuzzy Logic, Arduino, Ultrasonic Sensor</em></p><p align="center"><em> </em></p><p align="center"><strong><em>Abstrak <br /></em></strong></p><p><em>Pada era teknologi dan otomasi industri saat ini banyak digunakan robot sebagai alat bantu yang dapat meringankan pekerjaan manusia, sehingga dibutuhkan robot yang memiliki sistem pengendalian yang baik agar pekerjaan yang dilakukan oleh robot tersebut dapat lebih optimal. Perkembangan sistem pengendalian pada robot saat ini cukup pesat seiring dengan kebutuhan manusia yang semakin beragam. Beberapa metode banyak diterapkan pada sistem pengendalian robot secara otomatis. Logika fuzzy merupakan metode yang banyak digunakan dalam navigasi gerak robot. Sehingga pada penelitian ini akan diterapkan metode logika fuzzy dengan tipe Sugeno sebagai sistem navigasi robot yang ditanamkan pada mikrokontroler Arduino uno dan digunakan sensor ultrasonik sebagai nilai inputan jarak, pada masing – masing lintasan robot diberikan halangan sejauh 30 cm sehingga nilai pwm yang dihasilkan oleh robot dapat terukur. Hasil yang diperoleh pada penelitian ini adalah metode logika fuzzy Sugeno yang ditanamkan pada mikrokontroler Arduino uno dapat mengendalikan gerak robot dan menghindari halangan yang berada di sekitar lingkungan dengan baik.</em></p><strong><em>Kata kunci </em></strong><em>: Sistem Kendali, Navigasi, Logika Fuzzy, Arduino, Sensor Ultrasonik.</em>

scholarly journals Flood Detection System Using Ultrasonic Sensor with Fuzzy Logic Method

2021 ◽  
Author(s):  
Jessy Nasyta Putri Santoso ◽  
Tri Tisna Firly Hartini ◽  
Ali Suryaperdana Agoes
Keyword(s):  
Fuzzy Logic ◽  
Detection System ◽  
Ultrasonic Sensor ◽  
Fuzzy Logic Method ◽  
Flood Detection ◽  
Logic Method

PID plus fuzzy logic method for torque control in traction control system

2012 ◽  
Vol 13 (3) ◽  
pp. 441-450 ◽  
Author(s):  
H. -Z. Li ◽  
L. Li ◽  
L. He ◽  
M. -X. Kang ◽  
J. Song ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Torque Control ◽  
Traction Control ◽  
Traction Control System ◽  
Fuzzy Logic Method ◽  
Logic Method

scholarly journals Design of Parking Control Using Ultrasonic Sensor Based On Fuzzy Logic

2019 ◽  
Vol 3 (1) ◽  
pp. 155
Author(s):  
Insidini Fawwaz ◽  
Fadhillah Azmi ◽  
. Muhathir ◽  
N P Dharshinni
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Ultrasonic Sensor ◽  
Public Places ◽  
Proximity Sensor ◽  
Parking Lots ◽  
Fuzzy Methods ◽  
Infra Red ◽  
Parking Lot ◽  
Fuzzy Logic Method

<span>The number of vehicles in Indonesia is currently increasing, which is not matched by the availability of parking lots, especially cars. Like in public places, namely, offices, shops, and other public places. However, in Indonesia the use of parking lots is still less organized, such as too close the position of one car to another, the position of the vehicle that is not in line with the slot, this can cause inconvenience in the use of parking lots or both parties. Supervision carried out by the manager of the parking lot is still lacking because it can be caused by the vast parking area and the number of supervised vehicles, so that a parking control system is needed that can help overcome this problem. The control system to be designed uses a proximity sensor to detect the proximity of the vehicle to one another, where the position of the vehicle has been determined, not only to detect proximity, but the number of vehicles that have entered the parking area, so parking users know whether the slot provided is still available or not. To detect distance, fuzzy logic method is applied. Fuzzy methods are applied to read the conditions received by the proximity sensor, and calculate the number of vehicles using infra red and photodiode sensors. If information from the proximity sensor that is processed in the microcontroller by fuzzy logic is detected, the output is in the form of an LED indicator and alarm warning.</span>

scholarly journals Using WSR-88D Polarimetric Data to Identify Bird-Contaminated Doppler Velocities

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Yuan Jiang ◽  
Qin Xu ◽  
Pengfei Zhang ◽  
Kang Nai ◽  
Liping Liu
Keyword(s):  
Fuzzy Logic ◽  
Real Data ◽  
Radar Data ◽  
Second Step ◽  
Doppler Velocity ◽  
Data Quality Control ◽  
Fuzzy Logic Method ◽  
Automated Technique ◽  
Migrating Birds ◽  
Logic Method

As an important part of Doppler velocity data quality control for radar data assimilation and other quantitative applications, an automated technique is developed to identify and remove contaminated velocities by birds, especially migrating birds. This technique builds upon the existing hydrometeor classification algorithm (HCA) for dual-polarimetric WSR-88D radars developed at the National Severe Storms Laboratory, and it performs two steps. In the first step, the fuzzy-logic method in the HCA is simplified and used to identify biological echoes (mainly from birds and insects). In the second step, another simple fuzzy logic method is developed to detect bird echoes among the biological echoes identified in the first step and thus remove bird-contaminated velocities. The membership functions used by the fuzzy logic method in the second step are extracted from normalized histograms of differential reflectivity and differential phase for birds and insects, respectively, while the normalized histograms are constructed by polarimetric data collected during the 2012 fall migrating season and sorted for bird and insects, respectively. The performance and effectiveness of the technique are demonstrated by real-data examples.

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