CFP last date
22 April 2024
Reseach Article

Brushless DC Motor Speed Control using PID Controller, Fuzzy Controller, and Neuro Fuzzy Controller

by Ahmed K. Hassan, Mohammed S. Saraya, Mohamed S. Elksasy, Fayez F. Areed
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 30
Year of Publication: 2018
Authors: Ahmed K. Hassan, Mohammed S. Saraya, Mohamed S. Elksasy, Fayez F. Areed
10.5120/ijca2018916783

Ahmed K. Hassan, Mohammed S. Saraya, Mohamed S. Elksasy, Fayez F. Areed . Brushless DC Motor Speed Control using PID Controller, Fuzzy Controller, and Neuro Fuzzy Controller. International Journal of Computer Applications. 180, 30 ( Apr 2018), 47-52. DOI=10.5120/ijca2018916783

@article{ 10.5120/ijca2018916783,
author = { Ahmed K. Hassan, Mohammed S. Saraya, Mohamed S. Elksasy, Fayez F. Areed },
title = { Brushless DC Motor Speed Control using PID Controller, Fuzzy Controller, and Neuro Fuzzy Controller },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2018 },
volume = { 180 },
number = { 30 },
month = { Apr },
year = { 2018 },
issn = { 0975-8887 },
pages = { 47-52 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number30/29238-2018916783/ },
doi = { 10.5120/ijca2018916783 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:02:18.667820+05:30
%A Ahmed K. Hassan
%A Mohammed S. Saraya
%A Mohamed S. Elksasy
%A Fayez F. Areed
%T Brushless DC Motor Speed Control using PID Controller, Fuzzy Controller, and Neuro Fuzzy Controller
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 30
%P 47-52
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Brushless dc motors (BLDC motors) are commonly used nowadays in industry and at many applications according to its very high speed with a very compact size in comparison to the older motors with brushes, moreover the importance of being powered by direct current (DC) and without all disadvantages of using brushes, which is convenient to many applications like hard drivers, CD/DVD players, electric bicycles, electric and hybrid vehicles, CNC machines and Aero modeling. The purpose of this paper is to control the speed of a brushless dc motor by using PID controller, Fuzzy logic controller, and Neuro fuzzy controller. According to these varieties of control techniques which used to control the speed, we have many parameters which used to assess that which controller will be better to use.

References
  1. Ahmed, A. M., Ali-Eldin, A., Elksasy, M. S., & Areed, F. F. (2015). Brushless DC motor speed control using both PI controller and fuzzy PI controller. International Journal of Computer Applications, 109(10), 29-35.‏
  2. Mustafa, G. Y., Ali, A. T., Bashier, E., & Elrahman, M. F. (2013). Neuro-fuzzy controller design for a dc motor drive. University Of Khartoum Engineering Journal, 3(1).‏
  3. Tiwari, N., RITEE, R. C., & Diwan, R. Speed Control of Brushless DC Motor using Fuzzy and Neuro Fuzzy.‏
  4. Mosavi, M. R., Rahmati, A., Khoshsaadat, A., & Elektrotechniczny, P. (2012). Design of efficient adaptive neuro-fuzzy controller based on supervisory learning capable for speed and torque control of BLDC motor. PRZEGLĄD ELEKTROTECHNICZNY (Electrical Review), R, 88.‏
  5. Yashoda, M., & Sekhar, O. C. (2016). Design and Analysis of ANFIS based BLDC Motor. Indian Journal of Science and Technology, 9(35).‏
  6. Arulmozhiyal, R., & Kandiban, R. (2012, July). An intelligent speed controller for Brushless DC motor. In Industrial Electronics and Applications (ICIEA), 2012 7th IEEE Conference on (pp. 16-21). IEEE.‏
  7. Navaneethakkannan, C., & Sudha, M. (2016). Analysis and Implementation of ANFIS-based Rotor Position Controller for BLDC Motors. Journal of Power Electronics, 16(2), 564-571.‏
  8. Jang, J. S. (1993). ANFIS: adaptive-network-based fuzzy inference system. IEEE transactions on systems, man, and cybernetics, 23(3), 665-685.‏
Index Terms

Computer Science
Information Sciences

Keywords

BLDC Motor Speed Control PID Controller Fuzzy Controller Neuro fuzzy controller ANFIS.