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Optimizing PID control for automatic voltage regulators using ADIWACO PSO

Yaw Opoku Mensah Sekyere, Priscilla Oyeladun Ajiboye, Francis Boafo Effah, Bernard Tawiah Opoku

2025Scientific African13 citationsDOIOpen Access PDF

Abstract

This paper investigates the application of an enhanced Particle Swarm Optimization (PSO) variant, known as ADIWACO, for tuning Proportional-Integral-Derivative (PID) controllers in Automatic Voltage Regulator (AVR) systems. The ADIWACO PSO incorporates adaptive hyperbolic tangent functions for inertia weight and acceleration coefficients, effectively balancing exploration and exploitation during the optimization process. Using the Integral Time Absolute Error (ITAE) as the objective function, the proposed method achieves superior controller performance compared to existing optimization techniques, including BAT, Improved KIA, ARO, and BBO . The ADIWACO-tuned PID controller significantly reduces overshoot and settling time while enhancing system stability . Additionally, integrating a derivative filter with an optimally tuned coefficient further improves the AVR system's dynamic response. Stability analysis in the frequency domain confirms the robustness of the proposed approach. To validate its practicality, the method was applied to the IEEE 39-bus test system as a case study, demonstrating its effectiveness in real-world scenarios. The results underscore the potential of ADIWACO PSO to enhance the dynamic response and stability of AVR systems, offering a reliable and robust solution for engineering applications . This research contributes to advancing control system optimization and highlights the broader applicability of ADIWACO to complex systems requiring high-performance control solutions.

Topics & Concepts

PID controllerVoltage regulatorControl theory (sociology)Automatic controlControl engineeringVoltage regulationComputer scienceVoltageControl (management)EngineeringTemperature controlArtificial intelligenceElectrical engineeringAdvanced Control Systems DesignAdvanced Control Systems OptimizationControl Systems and Identification