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.

scholarly journals SPEED CONTROL OF DC MOTOR ON LOAD USING FUZZY LOGIC CONTROLLER (A CASE STUDY OF EMERGENCY LUBE OIL PUMP MOTOR OF H25 HITACHI TURBINE GENERATOR)

2017 ◽  
Vol 36 (3) ◽  
pp. 867-875
Author(s):  
II Ekpoudom ◽  
IE Archibong ◽  
UT Itaketo
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Expert Knowledge ◽  
Dc Motor ◽  
Project Work ◽  
Maximum Speed ◽  
Operating Pressure ◽  
Motor Speed ◽  
Turbine Generator ◽  
System A

This paper presents the development of a fuzzy logic controller for the driver DC motor in the lube oil system of the H25 Hitachi gas turbine generator. The turbine generator is required to run at an operating pressure of 1.5bar with the low and the high pressure trip points being 0.78 bar and 1.9 bar respectively. However, the driver DC motor speed drifted from the desired speed of 1450 revolutions per minutes (rpm) to as low as 1414 rpm. It is against this backdrop, that this project work was envisaged to design a controller capable of controlling the speed of the DC motor in order to achieve the desired speed rating of 1450 rpm. In modelling the motor, the transfer function method was used to develop a linear approximation to the actual motor. After computing the total inertia of the motor shaft, the motor model was simulated for the speed response in MATLAB and Simulink environment, and the response showed that the motor attained an actual maximum speed of 1414 rpm at settling time of 0.3 seconds.  Based on expert knowledge of the lube oil system, a fuzzy logic controller was designed and this resulted in the issuance of a control action to correct the actual speed of the motor from 1414 rpm to the desired speed of 1450 rpm.  http://dx.doi.org/10.4314/njt.v36i3.29

scholarly journals Evaluasi Performa Fuzzy Logic Controller untuk mengatur kecepatan Motor DC Penguatan Terpisah

2020 ◽  
Vol 12 (2) ◽  
pp. 100-110
Author(s):  
Muhammad Aditya Ardiansyah ◽  
Renny Rakhmawati ◽  
Hendik Eko Hadi Suharyanto ◽  
Era Purwanto
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Duty Cycle ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Boost Converter ◽  
Voltage Source ◽  
Single Output ◽  
Multiple Input ◽  
State Error

Beragamnya metode yang ditawarkan oleh fuzzy logic kontroller membuat sebagaian orang meneliti mengenai perbedaan metode inferensi yang digunakan oleh fuzzy logic controller. Sejauh ini terdapat tiga metode fuzzy logic kontroller yang telah dikembangkan yaitu Mamdani, Sugono dan Sukamoto. Pada jurnal ini penggunaan fuzzy logic kontroller akan dievaluasi dengan menggunakan motor dc penguat terpisah sebagai beban untuk melakukan pengaturan kecepatan motor dc. Pada paper ini tujuan utamanya adalah dapat mengendalikan kecepatan dari motor DC Penguatan Terpisah dengan mengatur tegangan jangkar dari motor tersebut. DC motor merupakan salah satu jenis motor memiliki banyak aplikasi dan memiliki kemudahan untuk mengatur kecepatan pada motor tersebut. Logika fuzzy yang digunakan pada studi ini adalah inferensi sugeno dimana dengan konfigurasi Multiple Input Single Output (MiSo). Dimana input berupa error dan perubahan error dan output berupa duty cycle dikarenakan yang dikendalikan oleh logika fuzzy adalah Boost Converter selaku controlled voltage source. Target pada jurnal ini adalah dari kecilnya nilai steady – state error dan minimnya osilasi sehingga mampu membuat sistem lebih stabil. Pada studi ini, Hasil pengujian dilakukan dengan menggunakan Simulink by Matlab dengan Hasil pengujian berupa error rata rata sebesar 5.36%.

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.

scholarly journals Execution of BLDC Motor using Fuzzy Logic Controller on Propulsion Application for Hybrid Vehicle System

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3989-3993
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Torque Ripple ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Rotor Speed ◽  
Brushless Dc Motors ◽  
Brushless Dc ◽  
Sensor Control

This research Paper proposes the Brushless DC motors control (BLDC) could accomplish higher execution looking into effectiveness in examination for old brushed DC motor controlling which is difficult to control because it requires a phase for switching circuit. This work proposes a fuzzy logic control for brushless DC motor for axis based on Hall Effect by applying sensor control system and also it produces brushless motor for rearranging the three phase conduction mode model. At long last this paper may be with create efficient control methodologies on enhance driving dynamics on the mechanical dynamic consider of propulsion method. The recommended control method stabilizes those controls services (speeds) done by controller of brushless DC motor drive (BLDC). On behalf of settling 2 wheels also physical favorable circumstances of BLDC motors are associated straight forwardly of the tires by improving the rotor speed. The parameters such as power factor, rotor speed, torque ripple, EMF is compensated & simulation results are tabulated.

scholarly journals Online Position Control Performance Improving Applying Incremental Fuzzy Logic Controller

2018 ◽  
Vol 248 ◽  
pp. 02005
Author(s):  
Dirman Hanafi ◽  
Mohamed Najib Ribuan ◽  
Wan HamidahWan Abas ◽  
Hidayat ◽  
Elmy Johana ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Motor Performance ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Peak Time ◽  
Control Performance ◽  
Position Control System

This paper presents the online control system application for improving the DC motor performance. DC motor widely used in industries and many appliances. For this aim fuzzy logic controller is applied. The type of fuzzy controller use is an incremental fuzzy logic controller (IFLC). The IFLC is developed by using MATLAB Simulink Software and implemented in online position control system applying RAPCON board as a platform. The experimental results produced the best gains of the IFLC are 1.785, 0.0056955 and 0.01 for error gain (GE), gain of change error (GCE) and gain of output (GCU) respectively. Its produce smaller rise time, peak time, 0% overshoot and smaller settling time. Beside that the IFLC response also able to follow the set point. The controller response parameters values are also acceptable. It means that the IFLC suitable to be use for improving the position control system performance.

Logistics Demand Forecasting with Asymmetry-Width Probabilistic Fuzzy Logic System

2013 ◽  
Vol 706-708 ◽  
pp. 2012-2016
Author(s):  
Zhong Wei Wang ◽  
Li Xin Lu
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Membership Function ◽  
Fuzzy Set ◽  
Demand Forecasting ◽  
Fuzzy Logic System ◽  
The Asymmetry ◽  
Logistics Demand ◽  
Better Than ◽  
Logic System

There are a lot of approaches in logistics demand forecasting field and perform different characters. The probabilistic fuzzy set (PFS) and probabilistic fuzzy logic system is designed for handling the uncertainties in both stochastic and nonstochastic nature. In this paper, an asymmetric probabilistic fuzzy set is proposed by randomly varying the width of asymmetric Gaussian membership function. And the related PFLS is constructed to be applied to a logistics demand forecasting. The performance discloses that the asymmetry-width probabilistic fuzzy set performs better than precious symmetric one. It is because the asymmetric probabilistic fuzzy sets variability and malleability is higher than this of the symmetric probabilistic fuzzy set.

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