Search Results for nonlinear-modeling

Abstract

Traditional Proportional-Integral-Derivative (PID) controllers continue to produce effective performance in controlling DC motors. Nowadays, advancements in optimization techniques are improving control performance. These techniques minimize fluctuations and accelerate convergence. In this study, the Particle Swarm Optimization (PSO) algorithm was applied using the Integral Time Absolute Error (ITAE) objective function. The PSO used to tune PID parameters in MATLAB/Simulink. The resulting PSO-PID performance was compared with that of a conventional PID controller. The findings indicate that the PSO-PID approach reduces peak overshoot errors from 2.1% to 0.5%. Moreover, the PSO-PID substantially decreases the settling time. Despite adding GA, PSO-PID already shows excellent results (0.93 s settling time, compared with 1.85 s in GA and 1.15 s in classical PID). These improvements contribute to smoother actuator voltage. It can also reduce mechanical and electrical issues and enhance long-term system reliability.