Automation on Washing Machine Using Fuzzy Logic Controller Provided with Three Input and Two Output for Setting the Temperature of Water

2021 ◽  
Author(s):  
K. Raja ◽  
S. Ramathilagam
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Washing Machine

scholarly journals Impact of pH of Water on Washing Time in Automatic Washing Machine

2018 ◽  
Vol 2 (1) ◽  
pp. 23-32
Author(s):  
M. Saqlain ◽  
F. R. Tariq
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Washing Machine ◽  
Washing Machines ◽  
Water Ph ◽  
Neutral Water

The pH of water is different in different areas. So, the washing machines which are based on Fuzzy Logic Controller being used in different areas are deprived of useful results because these machines cannot detect the pH of water. When pH of water is other than 7, more detergent and washing time for laundry is consumed. The proposition of the paper is that neutral water (pH = 7) should be used in washing machines. It will reduce the washing time. In this way, energy and washing time can be saved. The impersonate results and the action of the aforementioned device have been done by fuzzy logic toolbox using MATLAB.

Consumer’s Perception and Impact of pH on Detergent in Automatic Washing Machine Based on Fuzzy Logic Controller

2018 ◽  
Vol 02 (03) ◽  
pp. 31-40 ◽  
Author(s):  
Muhammad Saeed ◽  
◽  
Muhammad Saqlain ◽  
Naveed Jafar ◽  
◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Washing Machine ◽  
Consumer's Perception

scholarly journals Fuzzy-based Classification of Vaporous Compound using Electronic Nose

2019 ◽  
Vol 8 (12S2) ◽  
pp. 132-138
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Electronic Nose ◽  
Intelligent Systems ◽  
Fuzzy Logic Controller ◽  
Promising Method ◽  
Washing Machine ◽  
Lcd Display

The Fuzzy logic is a promising method in Artificial Intelligence. This is extensively employed to manage factors in the surroundings. The influence of fuzzy logic is demonstrated by evidence of making of proposed intelligent systems based on fuzzy logic methods e.g. pressure cooker, refrigerator, washing machine and so on. The intention of proposed work is to design an e-nose capable of detecting the distinct smell generated by various chemical vapours. These sensors of gas were used in this scheme. These readings from sensors passed to a fuzzy logic controller. The fuzzification process is taken by Mamdani style. The outcome of the proposed scheme is displayed at LCD display and matched to the outcome of simulation done using Matlab.

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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