Enhancing PID Controller Performance in RLC Circuits through Metaheuristic Optimization

Abstract

This research explores the application of Genetic Algorithms (GA) to optimize the performance of PID controllers in RLC circuits. The proposed methodology leverages the principles of natural selection, crossover, and mutation to iteratively refine the PID gains. The fitness of each individual is determined by its ability to minimize the Mean Square Error (MSE) for a unitary step response in the RLC circuit. The results demonstrate that the GA-based optimization approach yields significant improvements in the performance of PID controllers, achieving a significant reduction in the MSE for a unitary step response. This research highlights the importance of metaheuristic optimization techniques in the context of control systems, exemplifying their potential to enhance the performance of PID controllers in RLC circuits and beyond.