Dynamic Analysis of Low and Medium Maglev Train-Bridge System With Fuzzy PID Control

Abstract

In order to analyze the dynamic behavior of medium and low speed maglev train under different suspension control algorithms and effectively improve the robustness of the suspension control system, an optimized fuzzy PID controller is proposed based on the vehicle bridge coupling model of maglev train. The 23-dof (degree-of-freedom) vehicle model, the modeling of the electromagnetic suspension, and track irregularities are described, respectively. Furthermore, the fuzzy PID controller optimized by the genetic algorithm (GA) is addressed for the control of the dynamic response of the maglev system for complex dynamic conditions. Finally, the proposed controller is applied to the whole vehicle multipoint suspension platform for maglev train to verify the suspension performances in different operation conditions, including static and dynamic conditions. The results demonstrate that the introduction of GA has significantly improved the ride comfort of the maglev moving on the track under different operation conditions.