Authors :
Avijit Kundu; Saiful Islam Tuhin; Md. Sahadat Hossain Sani; Md. Wahidur Rahman Easin; Md. Arif Hasan Masum
Volume/Issue :
Volume 8 - 2023, Issue 8 - August
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/2s4949jr
DOI :
https://doi.org/10.5281/zenodo.8269112
Abstract :
This research paper thoroughly investigates
the performance characteristics of PID, which stands for
Proportional-Integral-Derivative, ANFIS, an acronym
for Adaptive-Neuro-Fuzzy Inference System, and ANN
(Artificial-Neural-Network) controllers in Automatic
Voltage Regulator (AVR) systems. This investigation
aims to analyze the controller's behavior so that it can be
used in any of the other control systems in the power
system. Leveraging the power of MATLAB-SIMULINK,
the PID controller undergoes meticulous tuning, while the
ANFIS and ANN controllers are trained using
meticulously curated data from the PID controller.Although the ANN
controller exhibits a reduction in overshoot compared to
the PID controller, it falls short with a lengthier settling-
time. Based on this comprehensive analysis, it is
unequivocally established that the ANFIS controller
reigns supreme, closely trailed by the ANN controller and
the PID controller. These findings offer profound insights
for researchers and practitioners, guiding them in the
astute selection of controllers for any control system.
Keywords :
AVR (Automatic-Voltage-Regulator), PID (Proportional Integral Derivative), ANFIS (Adaptive Neuro Fuzzy Inference System), ANN (Artificial-Neural-Network), Simulink, Controller, MATLAB, etc.
This research paper thoroughly investigates
the performance characteristics of PID, which stands for
Proportional-Integral-Derivative, ANFIS, an acronym
for Adaptive-Neuro-Fuzzy Inference System, and ANN
(Artificial-Neural-Network) controllers in Automatic
Voltage Regulator (AVR) systems. This investigation
aims to analyze the controller's behavior so that it can be
used in any of the other control systems in the power
system. Leveraging the power of MATLAB-SIMULINK,
the PID controller undergoes meticulous tuning, while the
ANFIS and ANN controllers are trained using
meticulously curated data from the PID controller.Although the ANN
controller exhibits a reduction in overshoot compared to
the PID controller, it falls short with a lengthier settling-
time. Based on this comprehensive analysis, it is
unequivocally established that the ANFIS controller
reigns supreme, closely trailed by the ANN controller and
the PID controller. These findings offer profound insights
for researchers and practitioners, guiding them in the
astute selection of controllers for any control system.
Keywords :
AVR (Automatic-Voltage-Regulator), PID (Proportional Integral Derivative), ANFIS (Adaptive Neuro Fuzzy Inference System), ANN (Artificial-Neural-Network), Simulink, Controller, MATLAB, etc.
