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.

An Advanced Fuzzy Logic Based Traffic Controller

2014 ◽  
Vol 5 (1) ◽  
pp. 31-40
Author(s):  
Bilal Ahmed Khan ◽  
Nai Shyan Lai
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Traffic Management ◽  
Fuzzy Logic Controller ◽  
Current Model ◽  
Traffic Signals ◽  
Processing Technique ◽  
Urban Traffic ◽  
Image Processing Technique ◽  
Traffic Light

Traffic light plays an important role in the urban traffic management. Therefore, it is necessary to improve the traffic controller for effective traffic management and better traffic flow leading to greener environment. In this paper, an advanced and intelligent traffic light controller is proposed, utilising the fuzzy logic technology and image processing technique. A fuzzy logic control has been implemented to provide the attribute of intelligence to the system. For real-time image acquisition, the process is further linked to the fuzzy logic controller which generates a unique output for each input pattern. Here image processing and fuzzy logic tool boxes of MATLAB are used where the final output is sent to Peripheral Interface Controller (PIC) microcontroller to drive the traffic signals in the desired manner. The results obtained show an improvement of 44% in the overall outcome of traffic management as compared to the conventional traffic controller, marking great feasibility and practicality of the current model.

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.

An Advanced Fuzzy Logic Based Traffic Controller

2015 ◽  
pp. 1490-1499
Author(s):  
Bilal Ahmed Khan ◽  
Nai Shyan Lai
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Traffic Management ◽  
Fuzzy Logic Controller ◽  
Current Model ◽  
Traffic Signals ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Traffic Light ◽  
Logic Control

Traffic light plays an important role in the urban traffic management. Therefore, it is necessary to improve the traffic controller for effective traffic management and better traffic flow leading to greener environment. In this paper, an advanced and intelligent traffic light controller is proposed, utilising the fuzzy logic technology and image processing technique. A fuzzy logic control has been implemented to provide the attribute of intelligence to the system. For real-time image acquisition, the process is further linked to the fuzzy logic controller which generates a unique output for each input pattern. Here image processing and fuzzy logic tool boxes of MATLAB are used where the final output is sent to Peripheral Interface Controller (PIC) microcontroller to drive the traffic signals in the desired manner. The results obtained show an improvement of 44% in the overall outcome of traffic management as compared to the conventional traffic controller, marking great feasibility and practicality of the current model.

A two-stage fuzzy logic controller for traffic signals

1999 ◽  
Vol 7 (6) ◽  
pp. 353-367 ◽  
Author(s):  
Mohamed B. Trabia ◽  
Mohamed S. Kaseko ◽  
Murali Ande
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Traffic Signals ◽  
Two Stage

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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