Stabilization of Electromagnetic Suspension System Behavior by Genetic Algorithm

Subject Areas : Renewable energy

Abbas Najar Khoda Bakhsh ¹ (Lecture/Islamic Azad University, Najafabad Branch)
Mohammad Reza Moradian ² (Lecture/Islamic Azad University, Najafabad Branch)
Laila Najar Khodabakhsh ³ (MSc/Yazd University)
Navid Reza Abjadi ⁴ (Assistant Professor/Shahrekord University)

Received: 2012-01-21 Accepted : 2012-09-02 Published : 2013-09-01

Keywords: Genetic Algorithm, MAGLEV, Electromagnetic Levitation,

Abstract :

Electromagnetic suspension system with a nonlinear and unstable behavior, is used in maglev trains. In this paper a linear mathematical model of system is achieved and the state feedback method is used to improve the system stability. The control coefficients are tuned by two different methods, Riccati and a new method based on Genetic algorithm. In this new proposed method, we use Genetic algorithm to achieve the optimum values of control coefficients. The results of the system simulation by Matlab indicate the effectiveness of new proposed system. When a new reference of air gap is needed or a new external force is added, the proposed system could omit the vibration and shake of the train coupe and so, passengers feel more comfortable.