Comparative Analysis of PID Tuning Methods for DC Motor Speed Control

In this paper, parameters of a proportional-integral-derivative (PID) controller used for the speed control of a DC motor are optimized using the particle swarm optimization (PSO) algorithm. The primary objective is to enhance the dynamic performance of the motor by minimizing steady-state error and improving response time. To evaluate the effectiveness of the PSO-based tuning, a comparative analysis is conducted against two well-known conventional tuning methods: Cohen-Coon and Ziegler-Nichols. The mean absolute error (MAE) is employed as the performance criterion, providing a quantitative measure of system accuracy under each tuning strategy. Simulation results demonstrate that the PSO-based approach significantly outperforms conventional methods, offering faster settling times and reduced error metrics. These findings highlight the potential of metaheuristic algorithms such as PSO in control system optimization, especially in applications where precision and adaptability are crucial.