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 Brushless DC Motor Speed Controller for Electric Motorbike

2018 ◽  
Vol 9 (2) ◽  
pp. 859
Author(s):  
Mohd Syakir Adli ◽  
Noor Hazrin Hany Mohamad Hanif ◽  
Siti Fauziah Toha Tohara
Keyword(s):  
Pid Controller ◽  
Dc Motor ◽  
Battery Pack ◽  
Brushless Dc Motor ◽  
Bldc Motor ◽  
Motor Speed ◽  
Brushless Dc ◽  
Speed Controller ◽  
Optimum Speed ◽  
Control Scheme

<p>This paper presents a control scheme for speed control system in brushless dc (BLDC) motor to be utilized for electric motorbike. While conventional motorbikes require engine and fuel, electric motorbikes require DC motor and battery pack in order to be powered up. The limitation with battery pack is that it will need to be recharged after a certain period and distance. As the recharging process is time consuming, a PID controller is designed to maintain the speed of the motor at its optimum state, thus ensuring a longer lasting battery time (until the next charge). The controller is designed to track variations of speed references and stabilizes the output speed accordingly. The simulation results conducted in MATLAB/SIMULINK® shows that the motor, equipped with the PID controller was able to track the reference speed in 7.8x10<sup>-2</sup> milliseconds with no overshoot.  The result shows optimistic possibility that the proposed controller can be used to maintain the speed of the motor at its optimum speed.</p>

scholarly journals Performansi Sistem Pengendali Kecepatan Motor BLDC Menggunakan Logika Fuzzy Logic

Jurnal METTEK ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 11
Author(s):  
Wayan Widhiada ◽  
Made Widiyarta ◽  
K.P. Arya Utama
Keyword(s):  
Fuzzy Logic ◽  
Power Supply ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Main Stream ◽  
Bldc Motor ◽  
Motor Speed ◽  
Brushless Dc ◽  
Simulation And Experiment ◽  
Dc Current

Brushless DC motor adalah salah satu jenis motor sinkron yang diberi arus DC yang bersumber dari inverter atau power supply. Motor AC menghasilkan arus AC yang dapat menggerakan motor. Pada dasarnya kecepatan motor dapat di atur menggunakan kontroler yang menghitung seberapa besar keluaran yang harus dihasilkan. Pada umumnya input dari kontroler berupa tuas (naik – turun atau putar) dan tombol untuk input awalnya. Oleh Karena itu dilakukan penelitian untuk mengganti input yang mengatur kecepatan motor BLDC. Kontrol kecepatan motor BLDC berbasis logika fuzzy adalah suatu system kontrol yang mengganti input main stream dari kontroler menjadi sensor beban, dan dimana pembacaanya akan dikontrol oleh logika fuzzy untuk mengatur control kecepatan motor BLDC. Penelitian dilakukan dengan dua cara yaitu simulasi dan eksperimen prototype dengan pemberian beban pada sensor yaitu 10 kg, 20 kg, 30 kg, 40 kg dan 50 kg sebagai inputnya. Hasil dari pengujian dan penghitungan yang didapat pada setiap pembebanan menghasilkan kecepatan yang stabil yaitu rata – rata 0.25 detik dengan kecepatan yang hamper setara dengan referensinya. Error pada kecepatan yang dihasilkan antara simulasi dan prototype sangat kecil yaitu kurang dari 1% pada masing – masing pembebanan. Brushless DC motor is one type of synchronous motor that is given a DC current from the inverter or power supply sourced. It produces an AC current that can drive the motor. Basically the motor speed can be set using a controller to compute the result of output. In general, the input from the controller is like a handle (up – down or twist) and a button for initial input. Therefore the research has changed the input that regulates the speed of the BLDC motor. BLDC motor speed is controlled based on fuzzy logic. Fuzzy logic is a control who help load sensor to replace the mainstream input like handle, and where the reader will be directed by logic to determine the speed of the BLDC motor. The research is carried out in two techniques, called simulation and experiment. The prototype is testing with the load on 10 kg, 20 kg, 30 kg, 40 kg and 50 kg as an input. The results of the tests is obtained at each loading resulted in a stable speed which is an average of 0.25 seconds with a speed that is almost the same as the reference. The error signal of the speed is produced between the simulation and prototype is very small, which is less than 1% in each load.

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 Adaptive proportional-integral fuzzy logic controller of electric motor drive

2021 ◽  
Vol 41 (2) ◽  
Author(s):  
Chiheb Ben Regaya ◽  
Fethi Farhani ◽  
Abderrahmen Zaafouri ◽  
Abdelkader Chaari
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Field Vector ◽  
Motor Drive ◽  
Proportional Integral ◽  
Speed Controller ◽  
Logic Control ◽  
Rotor Resistance ◽  
Resistance Variation ◽  
Electric Motor Drive

This paper presents the indirect field vector control of induction motor (IM) which is controlled by an adaptive Proportional-Integral (PI) speed controller. The proposed solution can overcome the rotor resistance variation, which degrades the performance of speed control. To solve this drawback, an adaptive PI controller is designed with gains adaptation based on fuzzy logic in order to improve the performances of IM with respect to parameters variations, particularly the rotor resistance (Rr). The proposed control algorithm is validated by simulation tests. The obtained results show the robustness towards the load torque disturbances and rotor resistance variation of the adaptive Proportional-Integral fuzzy logic control with respect to classical PI control, and adaptive control based on rotor resistance observer.

scholarly journals Real-time implementation of a novel hybrid fuzzy sliding mode control of a BLDC motor

2019 ◽  
Vol 10 (3) ◽  
pp. 1167
Author(s):  
Ali Mousmi ◽  
Ahmed Abbou ◽  
Yassine El Houm
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Hybrid Control ◽  
Sliding Mode ◽  
Fast Response ◽  
Bldc Motor ◽  
Tracking Accuracy ◽  
Brushless Dc Motors ◽  
Brushless Dc ◽  
Dc Motors

<span lang="EN-US">This paper presents a novel hybrid control of a BLDC motor using a mixed sliding mode and fuzzy logic controller. The objective is to build a fast and robust controller which overcome classical controllers’ inconveniences and exploit the fast response of brushless dc motors characterized by an intense torque and fast response time. First the paper study pros and cons of both sliding mode and fuzzy logic controllers. Then the novel controller and its stability demonstration are presented. Finally the proposed controller method is used for the speed control of a BLDC motor 3KW. The obtained results are compared with those of a fuzzy logic and a conventional sliding mode controller. It allows to show performance of the proposed controller in terms of speed response and reaction against disturbances, which is improved more than 5 times without losing stability or altering tracking accuracy</span>

scholarly journals A fuzzy logic controller based brushless DC motor using PFC cuk converter

2019 ◽  
Vol 10 (4) ◽  
pp. 1894 ◽  
Author(s):  
Sanatan Kumar ◽  
Debanjan Roy ◽  
Madhu Singh
Keyword(s):  
Fuzzy Logic ◽  
Power Factor ◽  
Fuzzy Logic Controller ◽  
Low Frequency ◽  
Dc Motor ◽  
Voltage Source ◽  
Brushless Dc Motor ◽  
Motor Speed ◽  
Cuk Converter ◽  
Brushless Dc

<span>This paper presents a PFC (Power Factor Correction) Cuk converter fed BLDC (Brushless DC) motor drive and the speed of BLDC motor is controlled using fuzzy logic implementation. The PFC converters are employed to enhance the power quality. The Brushless DC motor speed is under the control of DC-bus voltage of VSI-Voltage Source Inverter in which switching of low frequency is used. This helps in the electronic commutation of BLDC motors thus decreasing the switching losses in VSI. A DBR (Diode Bridge Rectifier) next to the PFC Cuk converter controls the voltage at DC link maintaining unity power factor. The characteristics of Cuk converter in four dissimilar modes of operation are studied such as continuous and discontinuous conduction modes (CCM and DCM) respectively. The entire system is simulated using Matlab/Simulink software and the simulation results are reported to verify the performance investigation of the proposed system.</span>

scholarly journals PERFORMANCE IMPROVEMENT ON MOTOR BLDC SPEED CONTROLLER BY USING MULTI CONTROLLER WITH SUMMATION TECHNIQUE

2021 ◽  
pp. 1-8
Author(s):  
Widjonarko ◽  
Cries Avian ◽  
Setya Widyawan Prakosa ◽  
Bayu Rudiyanto
Keyword(s):  
Control System ◽  
Fuzzy Logic Controller ◽  
Absolute Error ◽  
Bldc Motor ◽  
Motor Speed ◽  
Electric Cars ◽  
Speed Controller ◽  
The Difference ◽  
Increasing Demand ◽  
Artificial Neural Network Ann

BLDC motor is the most widely used in the industrial world, especially in electric vehicles. With this increasing demand, a variety of research topics emerged in BLDC motors. One popular research is on BLDC motor speed control topics to maintain speed for its application, such as intelligent cruise technology in electric cars and conveyors for line assembly. However, from several existing studies, the BLDC Motor controller still uses a single controller model. The controller's output is purely from the controller without any improvement in characteristics and has a problem with the oscillating speed setpoint (error problem). In this study, the researcher proposed a combining control with the concept of summation output to handle this problem. With this concept, the control techniques used can improve each other so that better control can be produced following the control system assessment parameters. The authors used a Fuzzy Logic Controller, Artificial Neural Network (ANN), and PID, which were combined and obtained seven control systems. The results show that the control system can improve several parameters using the summation concept from the seven controllers model. It has a positive overall correlation when viewed in terms of the difference between the Error and the setpoint or MAE (Mean Absolute Error) as parameter assessment.

scholarly journals Direct Torque Control System for a Three Phase Induction Motor With Fuzzy Logic Based Speed Controller

2010 ◽  
Vol 6 (2) ◽  
pp. 131-138
Author(s):  
Turki Abdalla ◽  
Haroution Hairik ◽  
Adel Dakhil
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Dynamic Performance ◽  
Direct Torque Control ◽  
Speed Control ◽  
Pi Controller ◽  
Torque Control ◽  
Speed Controller ◽  
Three Phase

This paper presents a method for improving the speed profile of a three phase induction motor in direct torque control (DTC) drive system using a proposed fuzzy logic based speed controller. A complete simulation of the conventional DTC and closed-loop for speed control of three phase induction motor was tested using well known Matlab/Simulink software package. The speed control of the induction motor is done by using the conventional proportional integral (PI) controller and the proposed fuzzy logic based controller. The proposed fuzzy logic controller has a nature of (PI) to determine the torque reference for the motor. The dynamic response has been clearly tested for both conventional and the proposed fuzzy logic based speed controllers. The simulation results showed a better dynamic performance of the induction motor when using the proposed fuzzy logic based speed controller compared with the conventional type with a fixed (PI) controller.

scholarly journals Soft Computing Technique of Bridgeless SEPIC Converter for PMBLDC Motor Drive

2018 ◽  
Vol 9 (4) ◽  
pp. 1503
Author(s):  
Meena Devi R. ◽  
L. Premalatha
Keyword(s):  
Control Method ◽  
Motor Drive ◽  
Bldc Motor ◽  
Motor Speed ◽  
Computing Technique ◽  
Brushless Dc ◽  
Speed Controller ◽  
Three Phase ◽  
Soft Computing Technique ◽  
Conduction Mode

A novel speed controller for the three-phase Brushless DC (BLDC) Motor Drive is proposed using a closed-loop AC-DC Bridgeless SEPIC Converter in continuous Conduction mode. This design proposes a single stage AC-DC converter with ON and OFF state equivalent circuits for 400W, 48V at 2450 rpm PMBLDC motor drive. The Fuzzy based voltage and current controlling method is proposed in this design. The voltage controlling method is used to control the speed for BLDC motor and the current controlling method is used to improve the power factor in AC supply. The speed of BLDC motor is observed with voltage disturbance and the constant motor speed is maintained. The proposed control method on SEPIC converter fed PMBLDC motor drive is modeled by Simulink/Matlab.

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.

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