Position tracking of DC motor with PID controller utilizing particle swarm optimization algorithm with Lévy flight and Doppler effect

Abstract

This paper presents the implementation of the particle swarm optimization with the Lévy flight Doppler effect (PSO-LFDE) algorithm for optimizing proportional-integral-derivative (PID) controller parameters in a direct current (DC) motor system. Traditional optimization algorithms like particle swarm optimization, whale optimization algorithm, grey wolf optimizer, and moth flame optimization often face challenges in balancing exploration and exploitation, leading to suboptimal performance. The proposed PSO-LFDE algorithm addresses these issues by incorporating Lévy flight for enhanced exploration and the Doppler effect for refined exploitation. The algorithm is validated using MATLAB/Simulink for position control in a DC motor system with step inputs of 10, 30, and 60 cm. Key performance metrics, including rise time, settling time, peak time, and steady-state error, were compared against other optimization methods. PSO-LFDE demonstrated superior performance, achieving a 41.63% improvement in rise time and a 70.20% reduction in peak time compared to other methods. These results highlight PSO-LFDE's effectiveness in optimizing PID controller parameters and improving the dynamic response of DC motor systems, offering a robust solution for real-world control applications.