Paper Info
Title
Adaptive Neuro-Fuzzy Inference System based speed controller for brushless DC motor.
Abstract
In this paper, a novel controller for brushless DC (BLDC) motor has been presented. The proposed controller is based on Adaptive Neuro-Fuzzy Inference System (ANFIS) and the rigorous analysis through simulation is performed using simulink tool box in MATLAB environment. The performance of the motor with proposed ANFIS controller is analyzed and compared with classical Proportional Integral (PI) controller, Fuzzy Tuned PID controller and Fuzzy Variable Structure controller. The dynamic characteristics of the brushless DC motor is observed and analyzed using the developed MATLAB/simulink model. Control system response parameters such as overshoot, undershoot, rise time, recovery time and steady state error are measured and compared for the above controllers. In order to validate the performance of the proposed controller under realistic working environment, simulation result has been obtained and analyzed for varying load and varying set speed conditions.
Year
DOI
Venue
2014
10.1016/j.neucom.2014.01.038
Neurocomputing
Keywords
Field
DocType
BLDC motor,Mathematical model of the BLDC motor,Proportional Integral controller,Fuzzy Variable Structure controller,Fuzzy Tuned PID controller,ANFIS controller
Control theory,PID controller,Control theory,Fuzzy logic,DC motor,Control system,Adaptive neuro fuzzy inference system,Open-loop controller,Mathematics,Electronic speed control
Journal
Volume
ISSN
Citations 
138
0925-2312
15
PageRank 
References 
Authors
0.95
2
2
Name
Order
Citations
PageRank
K. Premkumar1665.04
B. V. Manikandan2252.93