scholarly journals Simple Implementation of a Fuzzy Logic Speed Controller for a PMDC Motor with a Low Cost Arduino Mega

2020 ◽  
Vol 10 (2) ◽  
pp. 5419-5422
Author(s):  
K. S. Belkhir
Keyword(s):  
Fuzzy Logic ◽  
Flash Memory ◽  
Fuzzy Logic Controller ◽  
Low Cost ◽  
Computation Time ◽  
Motor Speed ◽  
Speed Controller ◽  
Simple Implementation ◽  
Speed Mode ◽  
Transient And Steady State

Control of the permanent magnetic direct current PMDC motor is a common practice, hence the importance of the implementation of the PMDC motor speed controller. The results of a fuzzy logic speed controller for the PMDC motor rely on an appropriate base. As the dimension of the rules increases, its difficulty rises which affects computation time and memory requirements. Fuzzy Logic Controller (FLC) can be carried out by a low-cost Arduino Mega which has a small flash memory and a maximum clock speed of 16MHz. It is realized by three membership functions and each was divided into three memberships. The results of the FLC are satisfactory, revealing superior transient and steady-state performance. In addition, the controller is robust to speed mode variations.

scholarly journals Optimal Tuning of Fuzzy Logic Controller Based Speed Control of DC Motor

2021 ◽  
Vol 19 (1) ◽  
pp. 77-80
Author(s):  
Mohsin A. Koondhar ◽  
Muhammad U. Keerio ◽  
Rameez A. Talani ◽  
Kamran A. Samo ◽  
Muhammad S. Bajwa ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Speed Control ◽  
Dc Motor ◽  
Motor Speed ◽  
Dc Motors ◽  
Manual Adjustment ◽  
Control Application ◽  
Installation Time ◽  
Transient And Steady State

Fuzzy logic controller (FLC) has become popular in the speed control application of DC motors with automatic adjustment function. In this article, the performance of a specific FLC controlled DC motor is studied. The exceed speed is observed with a stabilization time, thus confirming the FLC behavior. Therefore, FLC must be set to obtain the required performance by applying appropriate expert rules, the minimum overshoot and installation time can be maintained within the required values. With the help of FLC, the manual adjustment function is gradually eliminated, and the intelligent adjustment function is at the center position, and the performance is satisfactory. FLC DC motor speed control is implemented in MATLAB environment. The results show that the FLC method has the smallest bypass, smallest transient and steady-state error, and shows higher FLC efficiency as compared with other conventional controllers.

scholarly journals Comparison between Fuzzy Logic and PI Control for The Speed Of BLDC Motor

2018 ◽  
Vol 9 (3) ◽  
pp. 1116 ◽  
Author(s):  
Akram H. Ahmed ◽  
Abd El Samie B. Kotb ◽  
Ayman M. Ali
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dynamic Performance ◽  
Bldc Motor ◽  
Motor Speed ◽  
Proportional Integral ◽  
Brushless Dc ◽  
Speed Controller ◽  
Torque Response ◽  
High Degree

In this paper the analytical comparison of brushless DC (BLDC) motor drive with proportional integral (PI) and fuzzy logic controller (FLC) based speed controllers is estimated. Proportional integral (PI) has disadvantages like it do not operate properly when the system has a high degree of load disturbances.<em> </em>In recent years, the application of fuzzy logic controller (FLC) for high dynamic performance of motor drives has become an important tool. FLC is a good for load disturbances and can be easily implemented. The modeling and simulation of both the speed controllers have been made by MATLAB/SIMULINK. The dynamic characteristics of the BLDC motor (speed and torque) response, obtained under PI and Fuzzy logic based speed controller, are compared for various operating condition.

scholarly journals Development of Centrifugation Straining Control System for Greek Yogurt Production Based on Weight of Whey Drain

2020 ◽  
Vol 2 (1) ◽  
pp. 15-20
Author(s):  
Daniel Christianto ◽  
Cuk Supriyadi Ali Nandar ◽  
Widi Setiawan
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Process Time ◽  
Motor Speed ◽  
Speed Controller ◽  
Speed Up ◽  
And Control

Greek yogurt production needs a straining process that takes 10 hours or more. This paper proposes automation and control method for the centrifugation system to speed up the process time and to optimize the accuracy of quantity of whey drainage. Using system identification, the estimated mathematical model of straining process has been developed based on the traditional process of straining the yogurt. Then, the simulation and control design optimization has been carried out by using the estimated mathematical model. Based on the simulation results using whey mass controller, motor speed controller, and the combination of whey mass and motor speed controller, the controller that used are PID controller and fuzzy logic controller. The fastest controller is a PID controller as motor speed controller and fuzzy logic controller as whey mass controller that can speed up the production time and optimize the accuracy of quantity of whey drainage.

scholarly journals Exhaust Fan Speed Controller Using Fuzzy Logic Controller

2021 ◽  
Vol 1737 (1) ◽  
pp. 012046
Author(s):  
M Khairudin ◽  
Sigit Yatmono ◽  
Irdayanti M Nashir ◽  
Fatchul Arifin ◽  
W Aulia ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Speed Controller ◽  
Fan Speed

Hybrid Neural-Fuzzy Controller for Motorized Robot Arm

2011 ◽  
Vol 403-408 ◽  
pp. 5068-5075
Author(s):  
Fatma Zada ◽  
Shawket K. Guirguis ◽  
Walied M. Sead
Keyword(s):  
Fuzzy Logic ◽  
Design Methodology ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
System Response ◽  
Robot Arm ◽  
Neural Controller ◽  
Hybrid Controller ◽  
Neural Fuzzy ◽  
Transient And Steady State

In this study, a design methodology is introduced that blends the neural and fuzzy logic controllers in an intelligent way developing a new intelligent hybrid controller. In this design methodology, the fuzzy logic controller works in parallel with the neural controller and adjusting the output of the neural controller. The performance of our proposed controller is demonstrated on a motorized robot arm with disturbances. The simulation results shows that the new hybrid neural -fuzzy controller provides better system response in terms of transient and steady-state performance when compared to neural or fuzzy logic controller applications. The development and implementation of the proposed controller is done using the MATLAB/Simulink toolbox to illustrate the efficiency of the proposed method.

Fuzzy Hybrid Controller Model for Making Decision to Interpret Any Condition

2006 ◽  
Vol 111 ◽  
pp. 167-170
Author(s):  
M. Shahidul Karim ◽  
Rashed Mustafa
Keyword(s):  
Fuzzy Logic ◽  
Control Strategy ◽  
Room Temperature ◽  
Fuzzy Logic Controller ◽  
Low Cost ◽  
Electronic System ◽  
Comfort Level ◽  
Price Ratio ◽  
Hybrid Controller ◽  
Software Development System

The constantly increasing performance/price ratio of microcontrollers means electronic system can replace more and more electromechanical ones. In design, the goal is not to just replace the solution but also to improve it by adding new functionalities. The paper presents a model of industrial controller having possibility of the classical programming controller, with added elements of the fuzzy logic. Here fuzzy logic offers a technical control strategy that uses elements of everyday language. In this application, it is used to design a control strategy that adapts to the need of individual user. It achieves a higher comfort level and reduces energy consumption. Here we have used a fuzzy method which selects the contractions that best meet the specifications, where human knowledge is involved in a decision making process. With a fuzzy-logic software development system, the entire system, which includes conventional code for signal preprocessing as well as the fuzzy logic system, can be implemented on an industry-standard microcontroller. Using fuzzy logic on such a low-cost platform makes this a possible solution with most AC systems. Each home AC has a sensor that measures room temperature and compares it with the temperature set on the dial. The fuzzy logic controller uses a bimetallic switch and compares the set temperature with room temperature.

Low Cost Engine Management System (EMS) for the Cost Sensitive Two-Wheeler Application: Idle Speed and A/F Ratio Control Using PID and Fuzzy Logic Control Algorithms

2007 ◽  
Author(s):  
P. V. Manivannan ◽  
A. Ramesh
Keyword(s):  
Fuzzy Logic ◽  
Fuel Consumption ◽  
Fuzzy Logic Controller ◽  
Low Cost ◽  
Engine Management System ◽  
Position Sensor ◽  
Idle Speed ◽  
The Cost ◽  
Two Wheeler ◽  
Speed Fluctuations

In this work an Engine Management System (EMS) using a low cost 8-bit microcontroller specifically for the cost sensitive small two-wheeler application was designed and developed. Only the Throttle Position Sensor (TPS) and the cam position sensor (also used for speed measurement) were used. A small capacity 125CC four stroke two-wheeler was converted into a Port Fuel Injected (PFI) engine and was coupled to a fully instrumented Eddy Current Dynamometer. Air-fuel ratio was controlled using the open loop, lookup-table [speed (N) and throttle (α)] based technique. Spark Time was controlled using a proportional / fuzzy logic based close loop control algorithm for the idle speed control to reduce fuel consumption and emissions. Test results show a significant improvement in engine performance over the original carbureted engine, in terms of fuel consumption, emissions and idle speed fluctuations. The Proportional controller resulted in significantly lower speed fluctuations and HC / CO emissions than the fuzzy logic controller. Though the fuzzy logic controller resulted in low cycle by cycle variations than the original carbureted engine, it leads to significantly higher HC levels. The performance fuzzy logic can be improved by modifying the membership function shapes with more engine test data.

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 Design of microcontroller-based decentralized controller board to drive chiller systems using PID and fuzzy logic algorithms

2019 ◽  
Vol 234 (1) ◽  
pp. 98-107 ◽  
Author(s):  
Yalcin Isler ◽  
Savas Sahin ◽  
Orhan Ekren ◽  
Cuneyt Guzelis
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Low Cost ◽  
Variable Speed ◽  
Proportional Integral Derivative ◽  
Scroll Compressor ◽  
Proportional Integral ◽  
Output Controller ◽  
Expansion Valve ◽  
Controller Board

This study deals with designing a decentralized multi-input multi-output controller board based on a low-cost microcontroller, which drives both parts of variable-speed scroll compressor and electronic-type expansion valve simultaneously in a chiller system. This study aims to show the applicability of commercial low-cost microcontroller to increase the efficiency of the chiller system, having variable-speed scroll compressor and electronic-type expansion valve with a new electronic card. Moreover, the refrigerant system proposed in this study provides the compactness, mobility, and flexibility, and also a decrease in the controller unit’s budget. The study was tested on a chiller system that consists of an air-cooled condenser, a variable-speed scroll compressor, and a stepper driven electronic-type expansion valve. The R134a was used as a refrigerant fluid and its flow was controlled by electronic-type expansion valve in this setup. Both variable-speed scroll compressor and electronic-type expansion valve were driven by the proposed hardware using either proportional integral derivative or fuzzy logic controller, which defines four distinct controller modes. The experimental results show that fuzzy logic controlled electronic-type expansion valve and proportional integral derivative controlled variable-speed scroll compressor mode give more robustness by considering the response time.

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