Zahra Ramezani - Iran University of Science & Technology
N Riahi - Iran University of Science & Technology
Seyed Kamaleddin Mousavi Mashhadi - Iran University of Science & Technology, Member of Electrical Faculty

Numerous benefits of magnetic levitation (maglev) trains such as high speed, low energy consumption, no direct environmental pollution, high safety and reliability all together have made a great motivation for many countries to replace their old, transportation systems which need periodic costly maintenance with this innovative transportation.In this paper we aim to analysis the performance of a non-linear sliding mode control and a neural network in an adaptive controller on a magnetic levitation model (maglev). The proposed controller is an adaptive- neural procedure based on backstepping technique. Also, in the rest, sliding mode controller as a robust method is proposed and designed

Magnetic levitation (Maglev), Neural network, Adaptive controller, sliding mode controller