scholarly journals PERANCANGAN PROTOTYPE JEMURAN OTOMATIS MENGGUNAKAN SENSOR AIR DAN SENSOR LDR BERBASIS MIKROKONTROLER ARDUINO UNO DENGAN METODE FLC

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Nur Apipah Harahap
Keyword(s):  
Fuzzy Logic ◽  
Rainy Season ◽  
Fuzzy Logic Controller ◽  
Tropical Country ◽  
Arduino Uno ◽  
The Way ◽  
At Home

Indonesia is a tropical country that has two seasons, rainy and summer. when the rainy season arrives, the majority of people feel anxious when drying their clothes. The anxiety will increase when drying clothes but is outside the house, and at home, there are no people. From this incident, people were reluctant to hang clothes in the open, because they were afraid that their clothes would get wet when they were left by their owners while doing activities outside the house. FLC (Fuzzy Logic Controller) method is a method that only knows 0 and 1 in operation. The vague operation, there is no gray only black or white. And this is something logical. From the description of the problems that occur, the authors find the idea to make clothesline pullers that can work automatically, even though there are already some people who have made the same mechanism using Arduino Mega 2560, with just a dark and bright condition, here the author wants to try to renew the way the mechanism of the device works by using Arduino Uno, and look for conditions when the heat is hot but rain, then this method answers what must be done by applying the logic of Fuzzy Logic Controller inside the Arduino Uno microcontroller.

scholarly journals DC Motor Speed Control Using Mamdani Fuzzy Logic Based on Microcontroller

Jurnal Teknik ◽  
2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Sumardi Sadi
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Motor Speed ◽  
Logic Control ◽  
Control Command ◽  
Arduino Uno

DC motors are included in the category of motor types that are most widely used both in industrial environments, household appliances to children's toys. The development of control technology has also made many advances from conventional control to automatic control to intelligent control. Fuzzy logic is used as a control system, because this control process is relatively easy and flexible to design without involving complex mathematical models of the system to be controlled. The purpose of this research is to study and apply the fuzzy mamdani logic method to the Arduino uno microcontroller, to control the speed of a DC motor and to control the speed of the fan. The research method used is an experimental method. Global testing is divided into three, namely sensor testing, Pulse Width Modulation (PWM) testing and Mamdani fuzzy logic control testing. The fuzzy controller output is a control command given to the DC motor. In this DC motor control system using the Mamdani method and the control system is designed using two inputs in the form of Error and Delta Error. The two inputs will be processed by the fuzzy logic controller (FLC) to get the output value in the form of a PWM signal to control the DC motor. The results of this study indicate that the fuzzy logic control system with the Arduino uno microcontroller can control the rotational speed of the DC motor as desired.

Optimum Solar Panel Implementation Using DC-DC Boost Converter Controlled by Fuzzy Logic Controller

2015 ◽  
Vol 793 ◽  
pp. 378-382 ◽  
Author(s):  
Nurul Afiqah Zainal ◽  
Sasikala A.P. Ganaisan ◽  
Ajisman
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Voltage Divider ◽  
Boost Converter ◽  
Solar Panel ◽  
Maximum Power ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Arduino Uno ◽  
Power Point

This paper proposes the implementation of a simple fuzzy logic controller (FLC) for a DC-DC boost converter based on a microcontroller to obtain maximum power from the solar system with the maximum power point tracking (MPPT) method. The system includes a solar panel, DC-DC boost converter, the fuzzy logic controller implemented on Arduino Uno for controlling on/off time of MOSFET of the boost converter, voltage divider and optocoupler circuit. This paper presents a fuzzy logic real time code in the Arduino language for ATmega328 microcontroller on the Arduino UNO board. The designed system increases the efficiency of the solar panel based on experimental results.

scholarly journals Sistem Monitoring dan Kontrol Motor AC dengan Fuzzy Logic Controller Berbasis Arduino Uno

2021 ◽  
Vol 2 (1) ◽  
pp. 1-5
Author(s):  
Aifiayu Aifiayu ◽  
Ta'ali Ta'ali
Keyword(s):  
Fuzzy Logic ◽  
Power Supply ◽  
Fuzzy Logic Controller ◽  
Visual Basic ◽  
Drive Motor ◽  
Arduino Uno

Motor AC  merupakan motor yang paling banyak digunakan pada industry saat sekarang ini, dikarenakan Motor AC mempunyai sifat yang fleksibel. Selain itu terdapat  kekurangan pada Motor AC  salah satunya yaitu pada saat Motor AC diberikan beban maka torsi pada Motor AC menjadi besar, hal tersebut dapat mengakibatkan kecepatan Motor AC menurun. Maka dari itu penelitian ini bertujuan untuk mengontrolan dan monitoring yang dapat mesntabilkan kecepatan saat Motor berbeban dengan method Fuzzy Logic Controller. Pada  perancangan alat ini menggunakan softwere dan hardwere. Komponen hardwere yang digunakan ialah rangakaian power supply, Arduino Uno, sensor kecepatan, Gate Drive, Motor AC 1 Phasa dan softwere diantaranya softwere Arduino IDE yang berisi pemrograman bahasa C dalam mengatur kecepatan Motor AC 1 Phasa dan juga softwere Visual Basic  untuk memeonitoring kecepatan Motor AC. penelitian ini telah berhasil dalam menstabilkan kecepatan putaran motor saat ditambahkan beban bervariasi.

The Best Way to Access Gas Stations using Fuzzy Logic Controller in a Neutrosophic Environment

2020 ◽  
Vol 4 (1) ◽  
pp. 30-45
Author(s):  
Muhammad Naveed Jafar ◽  
Muhammad Saqlain ◽  
Aasia Mansoob ◽  
Asma Riffat
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Traffic Signals ◽  
Soft Sets ◽  
Gas Stations ◽  
Linguistic Input ◽  
Gas Station ◽  
The Way

These days, Google Map is used to find any location and/or to define the route to any given place. Its accuracy is up to 30 meters but if neutrosophic numbers are used, it gives more accuracy. To check the implementation of neutrosophic numbers in Google Map, a system is developed based on Fuzzy Logic Controller (FLC) using neutrosophic numbers to find the gas station which is nearest, less parking car units and with few traffic signals on the way. In this way, it takes less time to reach the available gas station. This system enables the driver to find a fuel station with more accuracy. We took five linguistic inputs including distance, gas availability, parking car unit, amount of gas, and the number of traffic signals to get one output, that is, time. We assigned different neutrosophic soft sets to each linguistic input. FLC inference was designed using 108 rules based on if-then statements to select time to reach the gas station. The results were verified by MATLAB’s Fuzzy Logic Toolbox.

Application Fuzzy Logic System for Accurate Sheet Trim Shower Position

2019 ◽  
Vol 3 (1) ◽  
pp. 186-192
Author(s):  
Yudi Wibawa
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Automation System ◽  
Paper Making ◽  
System A ◽  
Accurate Position ◽  
And Performance ◽  
Better Than ◽  
Logic System

This paper aims to study for accurate sheet trim shower position for paper making process. An accurate position is required in an automation system. A mathematical model of DC motor is used to obtain a transfer function between shaft position and applied voltage. PID controller with Ziegler-Nichols and Hang-tuning rule and Fuzzy logic controller for controlling position accuracy are required. The result reference explains it that the FLC is better than other methods and performance characteristics also improve the control of DC motor.

STABILISASI TEGANGAN KELUARAN BUCK CONVERTER DENGAN METODE FUZZY LOGIC CONTROLLER

JURNAL ELTEK ◽  
2018 ◽  
Vol 16 (2) ◽  
pp. 125
Author(s):  
Oktriza Melfazen
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Rise Time ◽  
Fuzzy Logic Controller ◽  
Buck Converter ◽  
Settling Time

Buck converter idealnya mempunyai keluaran yang stabil, pemanfaatandaya rendah, mudah untuk diatur, antarmuka yang mudah dengan pirantiyang lain, ketahanan yang lebih tinggi terhadap perubahan kondisi alam.Beberapa teknik dikembangkan untuk memenuhi parameter buckconverter. Solusi paling logis untuk digunakan pada sistem ini adalahmetode kontrol digital.Penelitian ini menelaah uji performansi terhadap stabilitas tegangankeluaran buck converter yang dikontrol dengan Logika Fuzzy metodeMamdani. Rangkaian sistem terdiri dari sumber tegangan DC variable,sensor tegangan dan Buck Converter dengan beban resistif sebagaimasukan, mikrokontroler ATMega 8535 sebagai subsistem kontroldengan metode logika fuzzy dan LCD sebagai penampil keluaran.Dengan fungsi keanggotaan error, delta error dan keanggotaan keluaranmasing-masing sebanyak 5 bagian serta metode defuzzifikasi center ofgrafity (COG), didapat hasil rerata error 0,29% pada variable masukan18V–20V dan setpoint keluaran 15V, rise time (tr) = 0,14s ; settling time(ts) = 3,4s ; maximum over shoot (%OS) = 2,6 dan error steady state(ess) = 0,3.

Performance Comparison of MANET, VANET and FANET

2018 ◽  
Vol 8 (5) ◽  
pp. 132
Author(s):  
Aarti Sahu ◽  
Laxmi Shrivastava
Keyword(s):  
Fuzzy Logic ◽  
Wireless Network ◽  
Packet Loss ◽  
Ad Hoc Network ◽  
Fuzzy Logic Controller ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Performance Comparison ◽  
Fuzzy Rules ◽  
Mobile Ad Hoc

A wireless ad hoc network is a decentralized kind of wireless network. It is a kind of temporary Computer-to-Computer connection. It is a spontaneous network which includes mobile ad-hoc network (MANET), vehicular ad-hoc network (VANET) and Flying ad-hoc network (FANET). Mobile Ad Hoc Network (MANET) is a temporary network that can be dynamically formed to exchange information by wireless nodes or routers which may be mobile. A VANET is a sub form of MANET. It is an technology that uses vehicles as nodes in a network to make a mobile network. FANET is an ad-hoc network of flying nodes. They can fly independently or can be operated distantly. In this research paper Fuzzy based control approaches in wireless network detects & avoids congestion by developing the ad-hoc fuzzy rules as well as membership functions.In this concept, two parameters have been used as: a) Channel load b) The size of queue within intermediate nodes. These parameters constitute the input to Fuzzy logic controller. The output of Fuzzy logic control (sending rate) derives from the conjunction with Fuzzy Rules Base. The parameter used input channel load, queue length which are produce the sending rate output in fuzzy logic. This fuzzy value has been used to compare the MANET, FANET and VANET in terms of the parameters Throughput, packet loss ratio, end to end delay. The simulation results reveal that usage of Qual Net 6.1 simulator has reduced packet-loss in MANET with comparing of VANET and FANET.

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