Comparison Performances of PSO and GA to Tuning PID Controller for the DC Motor

Abstract

A DC motor widely uses for sensitive speed and position in industry. Stability and productivity of a system are important for controlling of a DC motor speed. Stable of speed which affected from load fluctuation and environmental factors. Therefore, it is important for the speed value which is required as constant and to keep it as its value. In this study, it is aimed that the speed value which is achieved as required value and keeping it as constant using Proportional, Integral and Derivative (PID) controller for tuning parameters. Firstly, Ziegler-Nichols (ZN) is one of a traditional method used. PID parameters are determined with responses of open-loop under running system. Later, parameters of the PID are estimated using two metaheuristic algorithms such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). As a result, three algorithms’ results are compared based on five criteria.  The PSO algorithm produces better results than Genetic Algorithm for each criteria.