Comparative study of GA, PSO, and DE for tuning position domain PID controller

Abstract

Gain tuning is very important in order to obtain good performances for implementing a controller. In this paper, three popular evolutionary algorithms are utilized to optimize the control gains of a position domain PID controller for the improvement of contour tracking for robotic manipulators. Differential Evolution (DE), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to optimize the gains of the controller and three distinct fitness functions are also used to quantify the contour performance of each solution set. Simulation results show that PSO was proven to be quite efficient for the linear contour, while DE featured the highest performance for the nonlinear case. Both algorithms performed consistently better than GA that featured premature convergence in all cases.