Genetic Algorithm Tuned Super Twisting Sliding Mode Controller for Suspension of Maglev Train with Flexible Track

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