Brushless motors have come to monopolize over many applications such as automobile industries, medical instruments, aerospace applications etc. The features such as high power density, high reliability, compact size, wide range of speed control etc make brushless dc (BLDC) motor distinct from other motors. The ordinary control methods of BLDC conduce high ripples in torque and speed. Here an unaccustomed method is used for controlling the BLDC motor. A firefly algorithm technique with proportional-integral-derivative (PID) controller is used to elevate the dynamic control of BLDC motor. Compared to any other optimization techniques, firefly algorithm (FA) is most effective tool and it gives surpassing performance in the field of optimization. Here PID controller based FA technique is used, which results in torque and speed ripple reduction, and gives a better output.
Skip Nav Destination
,
Article navigation
15 April 2020
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MICROELECTRONICS, SIGNALS AND SYSTEMS 2019
27–28 September 2019
Kollam, India
Research Article|
April 15 2020
Speed and torque control of BLDC motor using firefly algorithm technique Available to Purchase
C. K. Karthika;
Peter Abraham
C. K. Karthika
1,a)
Peter Abraham
1,b)
1
EEE Department, RIT Kottayam
, India
AIP Conf. Proc. 2222, 040013 (2020)
Citation
C. K. Karthika, Peter Abraham; Speed and torque control of BLDC motor using firefly algorithm technique. AIP Conf. Proc. 15 April 2020; 2222 (1): 040013. https://doi.org/10.1063/5.0003970
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Citing articles via
The implementation of reflective assessment using Gibbs’ reflective cycle in assessing students’ writing skill
Lala Nurlatifah, Pupung Purnawarman, et al.
Effect of coupling agent type on the self-cleaning and anti-reflective behaviour of advance nanocoating for PV panels application
Taha Tareq Mohammed, Hadia Kadhim Judran, et al.
Classification data mining with Laplacian Smoothing on Naïve Bayes method
Ananda P. Noto, Dewi R. S. Saputro
Related Content
Fast response antiwindup self tuning fuzzy PID speed control of brushless DC motor drive
AIP Conf. Proc. (April 2020)
Particle swarm optimization based PID controller tuning for speed control BLDC system
AIP Conf. Proc. (July 2024)
A comparison study of various control algorithms for BLDC motor iin robotic applications
AIP Conf. Proc. (December 2022)
A review on artificial intelligence based control techniques on controlling BLDC motor measures
AIP Conf. Proc. (July 2023)
Fuzzy based MPPT system for driving BLDC motor
AIP Conf. Proc. (April 2020)