Improving DC Voltage Regulation using Optimal PID Controller Based on Particle Swarm Optimization Algorithm

Regulated direct current (DC) is essential for numerous applications like renewable energy systems, electronics, and transportation. Achieving accurate, stable, and responsive DC regulation presents a significant challenge. This paper investigates the implementation of a Proportional-Integral-Derivative (PID) controller and explores its parameter tuning using the Particle Swarm Optimization (PSO), and Gray wolf optimization GWO methods. The dynamic response characteristics of PID based on controller is compared against both a conventional PID controller tuned by Ziegler-Nichols tuned method and gray wolf optimization (GWO) algorithm. The dynamic response characteristics of PID based on controller is compared against both a conventional PID controller tuned by Ziegler-Nichols tuned method and gray wolf optimization (GWO) algorithm through simulations in MATLAB 2020. Simulation results demonstrate that the PSO-tuned PID controller achieves superior performance with significant improvements in key metrics. The rise time is drastically reduced from 5.4978e-04 seconds to 4.6743e-10 seconds, the settling time drops from 0.0075 seconds to 8.323e-10 seconds, and the overshoot is effectively eliminated, approaching near zero. This work highlights the advantages of PSO-based PID tuning for achieving precise and efficient DC regulation.