The suspension air-gap of Maglev train needs controller for it is inherently unstable and highly nonlinear. To maintain a high quality of ride, comfort and safety for the passengers the train suspension controller must maintain the suspension air-gap. During operation the suspension air-gap of a Maglev train is only in millimeters. This easily causes instability under excitation of nonlinear load and track tiny deformation. Additionally, a track with a low stiffness will experience larger bending displacement and result in high vibrations. A high stiffness track experience minor bending displacement, which will diminish the vibration and improve riding quality. Unfortunately, using high stiffness guideway track is expensive. Instead, by designing a good controller the low stiffness material can be used. In this paper genetic algorithm tuned super twisting sliding mode control is proposed for it offers a good controlling ability since it is insensitive to external disturbance, parameter variation and has a fast dynamic response. The proposed controllers are tested under different circumstances, i.e., Maglev train with rigid track and with flexible track under variable load and external random disturbance.INDEX TERMS Flexible track, genetic algorithm, Maglev train, sliding mode control, super twisting sliding mode control and suspension air-gap.
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