Controlling the navigation of automatic guided vehicle (AGV) using integrated fuzzy logic controller with programmable logic controller (IFLPLC)—stage 1

2009 ◽  
Vol 47 (5-8) ◽  
pp. 795-807 ◽  
Author(s):  
Mehdi Yahyaei ◽  
J. E. Jam ◽  
R. Hosnavi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Programmable Logic Controller ◽  
Programmable Logic ◽  
Automatic Guided Vehicle ◽  
Stage 1

scholarly journals Fuzzy proportional-integral speed control of switched reluctance motor with MATLAB/Simulink and programmable logic controller communication

2019 ◽  
Vol 52 (7-8) ◽  
pp. 1137-1144 ◽  
Author(s):  
Ali Uysal ◽  
Serdar Gokay ◽  
Emel Soylu ◽  
Tuncay Soylu ◽  
Serkan Çaşka
Keyword(s):  
Fuzzy Logic ◽  
Control Algorithm ◽  
Programmable Logic Controller ◽  
Programmable Logic ◽  
Matlab Simulink ◽  
Switched Reluctance ◽  
Proportional Integral ◽  
Reluctance Motor ◽  
Integral Controller ◽  
Proportional Integral Controller

In this study, the auto-tuning proportional-integral controller is used to control the speed of a switched reluctance motor. The control algorithm is executed by the programmable logic controller. The proportional integral gains are determined via fuzzy logic. Fuzzy logic is executed on a separate computer via MATLAB/Simulink software. The data exchange between the programmable logic controller and MATLAB/Simulink is done with object linking embedding/component for the process. The fuzzy proportional integral control algorithm is compared with the conventional proportional integral controller. We reduced the load on the programmable logic controller via executing fuzzy logic in a separate computer and at the same time eliminated the disadvantages of the conventional proportional-integral controller. With the proposed method, the engine reached the reference speed value in a short time and the overshoots were eliminated in variable conditions such as different load and different speed conditions.

scholarly journals Pengatur Intensitas Cahaya Ruangan dengan Metode Fuzzy Logic Menggunakan PLC

2019 ◽  
Vol 1 (3) ◽  
pp. 100
Author(s):  
Arif Budi Setiawan ◽  
Riky Dwi Puriyanto
Keyword(s):  
Fuzzy Logic ◽  
Energy Use ◽  
Programmable Logic Controller ◽  
Programmable Logic ◽  
Centroid Method ◽  
Lighting Control ◽  
Logic Control ◽  
Non Linear ◽  
Solar Lighting ◽  
Lighting Systems

Sistem penerangan ruangan konvensional kurang efisien dalam penggunaan energi karena hanya menggunakan prinsip menyalakan (on) dan mematikan (off) lampu serta tidak menghiraukan pengaruh dan kontribusi dari luar atau pencahayaan matahari. Untuk mengatasi permasalahan tersebut dibuatlah sistem pengendalian cahaya lampu penerangan secara otomatis menggunakan Programmable Logic Controller (PLC) Omron sebagai pengendali. Proses pengendalian intensitas cahaya lampu, pada ruangan memanfaatkan dua sensor cahaya berjenis Light Dependent Resistance (LDR) dengan menggunakan metode fuzzy Sugeno sebagai cara pengambilan keputusan dengan dua himpunan dan tiga variabel disetiap himpunan, sedangkan untuk mengubah kembali ke bentuk bilangan crisp atau defuzzyfikasi menggunakan metode Centroid. Kendali fuzzy logic sangat tepat digunakan untuk pengendalian sistem yang bersifat non-linear dan adaptif. Berdasarkan hasil pengujian, sistem yang dibangun dapat berjalan dengan baik dengan tingkat akurasi pengendalian sebesar 99,38% yang diperoleh dari perbandingan antara pengujian sistem langsung dan pengujian dengan Matlab.Conventional room lighting systems are less efficient in energy use because they only use the principle of turning on (off) and turning off (off) lights and ignoring the influence and contribution of outside or solar lighting. To overcome these problems, a lighting control system was made automatically using the Omron Programmable Logic Controller (PLC) as a controller. The process of controlling light intensity, in a room utilizing two light sensors, type Light Dependent Resistance (LDR) using the Sugeno fuzzy method as a way of making decisions with two sets and three variables in each set, while to change back to the form of crisp numbers or defuzzification using the Centroid method. Fuzzy logic control is very appropriate to be used for controlling systems that are non-linear and adaptive. Based on the test results, the system built can run well with a level of accuracy of control of 99.38% obtained from the comparison between direct system testing and testing with Matlab.

scholarly journals Control response of electric demand by means of fuzzy logic using programmable logic controller (PLC)

2013 ◽  
Vol 8 (20) ◽  
pp. 1058-1067 ◽  
Author(s):  
L Rojas Renteriacute a J ◽  
Macias Bobadilla G ◽  
Luna Rubio R ◽  
A Gonzalez Gutierrez C ◽  
Rojas Molina A ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Programmable Logic Controller ◽  
Programmable Logic ◽  
Control Response

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.

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