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Jabari, M., Ekinci, S., Izci, D., Bajaj, M. and Zaitsev, I. (2024) Efficient DC Motor Speed Control Using a Novel Multi-Stage FOPD(1+PI) Controller Optimized by the Pelican Optimization Algorithm. Scientific Reports, 14, Article No. 22442.
https://doi.org/10.1038/s41598-024-73409-5

has been cited by the following article:

• TITLE: Modeling and Simulation of AVR Systems in MATLAB/Simulink: Performance Comparison of PID and ANN Controllers

  AUTHORS: Ahmad Fakhrul Arif Mohd Yusre, Siti Nor Atirah Samuji, Nurul Syuhada Mohd Shari, Norshaza Atika Saidin, Nur Azura Noor Azhuan

  KEYWORDS: Automatic Voltage Regulator (AVR), PID Controller, Artificial Neural Network (ANN), Power System Stability

  JOURNAL NAME: Journal of Power and Energy Engineering, Vol.13 No.9, September 24, 2025

  ABSTRACT: This study presents the design and modeling of an Automated Voltage Regulator (AVR) using MATLAB/Simulink, with a comparative performance evaluation against Proportional-Integral-Derivative (PID) and Artificial Neural Network (ANN) controllers. Voltage regulation is crucial to ensure reliable and stable power delivery under varying load conditions. In this work, a dynamic system model was developed to represent the electrical network, followed by the implementation of control algorithms to maintain output voltage within acceptable limits. The proposed approach was assessed through extensive simulations under multiple operating conditions and disturbances. The results demonstrate that ANN-based control outperforms both conventional AVR and PID controllers in terms of peak time, settling time, rise time, and overshoot percentage. Furthermore, ANN provides superior stability and adaptability in handling load variations, establishing it as the most effective control strategy for voltage regulation.