Design and implementation of a controller for magnetic levitation system using genetic algorithms

This research presents an optimum approach for designing of controller parameters for an unstable system using Genetic Algorithms (GA). The design goal is to minimize the integral absolute error and reduce transient response by minimizing overshoot settling time and rise time of step response. We define an objective function of these indexes. Then by minimizing the function using binary and real-coded GA, the optimal controller parameters can be assigned. In this study, a magnetic levitation system is considered as a case study and the controller is designed to keep a magnetic object suspended in the air counteracting the weight of the object. The proposed algorithms are implemented using xPCtarget® toolbox and Simulink® which facilitate to utilize hardware in the loop (HIL) property, Tele-lab implementation and fast prototyping approoch. Simulation and experimental results show the effectiveness and robustness of the proposed methods which are applicable to various control systems. Also, binary and real-coded performances are compared and discussed. © 2008 Asian Network for Scientific Information.