Design and Implementation of Fractional-Order PID Controller for Magnetic Levitation System Using Genetic Algorithm-Based Optimization

Abstract

Magnetic levitation (Maglev) systems have become a field of interest in last couple of decade due to no friction and low energy consumption. Such systems are having much attraction because of their practical applications and importance in control engineering. In this paper, we are dealing with the design and implementation of an integer-order PID and Fractional-Order PID (FOPID) controller for controlling magnetic levitation system. It has been observed that, by nature, magnetic levitation system is highly nonlinear and unstable. The performance of PID and FOPID controller is improved by Genetic Algorithm (GA)-based optimization technique. The parameters of controllers are tuned by minimizing the chosen performance index ITAE of the system. Finally, comparison of PID and FOPID controller is done on the basis of performance parameters. It is found that FOPID controller gives more precise results than PID controller.