Evaluation And Optimization Of Control System For Maglev Platform

Because the magnetic levitation platform has no friction and can control the suspension height,the magnetic levitation platform is selected to simulate the non gravity environment in space.The magnetic force between the magnetic pole and the guide rail is used to balance the gravity of the whole system,so that the platform has a long linear motion without collision and frictionless along the guide rail.In order to test the performance of the constructed Maglev Platform,the study was conducted to evaluate the performance of the magnetic levitation system.In the experiment,the levitate system appeared the pitching problem and the heavy weight single pendulum because of its lack of robustness.The theoretical analysis of the magnetic levitation control model finds that the robustness is not enough because a series of simplification is made in the calculation process of the structural Maglev control system,which leads to the controller parameters obtained only by the trial and error method.This makes the robustness of the magnetic levitation device more disadvantageous than the theoretical one.In view of the single pendulum oscillation phenomenon in magnetic levitation experiment,the negative damping of the system is analyzed from the low frequency oscillation of the pendulum.When the pendulum length is longer,the lower the oscillation frequency,the more negative damping the system will be.This study proposes a viscous damping force method at the suspension point.The experimental results show that the damping of the system with viscous damping increases and the robustness is improved.In view of the problem that the model of the magnetic levitation system can not be accurately calculated,the BP algorithm in the neural network is used to identify the data obtained by the experiment,and the network model of the controlled object is more accurate than the simplified mathematical model.The new control system is constructed with the neural network PID instead of the original controller,and the model simplification processing in the traditional Maglev system design process is solved.The control parameters of the simplified model are not perfectly matched to the actual magnetic suspension system,and the system robustness is improved.In order to ensure the smoothness of the operation of the Maglev Platform,it is of great importance to evaluate and optimize the control system of the Maglev Platform.