Year: 2024
Type: article
Abstract: This research paper provides an in-depth analysis of the performance characteristics of PID (Proportional-Integral-Derivative) and ANFIS (Adaptive Neuro-Fuzzy Inference System) controllers within Automatic Voltage Regulator (AVR) systems. The primary objective is to evaluate these controllers' behavior and efficacy, potentially extending their application to other control systems in the power sector. Utilizing the robust capabilities of MATLAB-SIMULINK, the PID controller was finely tuned, while the ANFIS controller was trained using carefully selected data. The findings highlight the ANFIS controller's exceptional performance, characterized by a notably fast settling time of 1.7277 seconds and 1.8716% overshoot. In comparison, the PID controller exhibited greater overshoot and a longer settling time, demonstrating less efficiency. These results were compared with other published research papers, further validating the superior performance of the ANFIS controller. This detailed evaluation confirms the ANFIS controller's superiority, offering significant guidance for researchers and industry professionals in making informed decisions regarding the optimal choice of controllers for various control systems.
Source: OODBODHAN
Authors: Sajesan Ghimire, Bhriguraj Bhattrai, Sulav Shrestha, Sagar Poudel
Institutions: Tribhuvan University, Institute of Engineering
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4407750301