IMPLEMENTATION OF HYBRID PID CONTROLLER BASED ON GENETIC ALGORITHMS FOR MODULAR SYSTEM POSITION CONTROL

Abstract

An examination of the nonlinear characteristics of DC servomotors, along with the design challenges and mechanical variations associated with different operating conditions reveals that a conventional Proportional – Integral – Derivative (PID) controller alone cannot achieve precise control. This study introduces an enhanced approach to optimize DC motor control in position mode by minimizing transient response characteristics including overshoot, rising time (t_r), and settling time (t_S). A genetic algorithm (GA) was employed to determine the optimal self-tuning parameters for K_P, K_I, and K_D. The study was conducted in three phases; first, the system was configured using the standard controller; second, the standard controller was replaced with the GA algorithm, with the integral time absolute error (ITAE) selected for the performance criterion for the DC servomotor control system; finally, a hybrid controller was developed by integrating the GA controller with the standard controller. Simulation results indicate that this dual controller achieves remarkable accuracy in control response, with a minimal overshoot increase of 1.667%, a 19.83% reduction in rise time (t_r), a 29.18% decrease in settling time (t_S) and a steady state error of 9.373% for the DC servomotor in position mode.