Research On The Control Method Of Magnetic Levitation Bearing

Magnetic levitation bearings are widely used in machine tool spindles,aerospace and other fields because of their advantages of contactless,frictionless,long working life and high accuracy.As the core module in the magnetic levitation bearing system,the controller’s control algorithm directly affects the dynamic performance and stability of the system.The traditional sliding mode control algorithm in the control of magnetic levitation bearings has the problems of large error offset and jitter vibration phenomenon,which limit its application in the control field.Therefore,it is important to design a stable,fast and robust control algorithm for magnetic levitation bearings.In this thesis,a sliding mode controller based on exponential convergence law is designed and optimized by RBF neural network sliding mode control algorithm,and a second-order sliding mode control algorithm is introduced to better suppress jitter.The details are as follows:Firstly,from the working principle and composition structure of magnetic levitation bearing system,the mathematical model of single-degree-of-freedom magnetic levitation bearing is established through reasonable simplification and force analysis of the structure of magnetic levitation bearing,and on its basis,the mathematical model of radial four-degree-of-freedom magnetic levitation bearing is established and described in the form of state-space equation and transfer function to provide theoretical support for the subsequent research and experiment.Secondly,the control principles of exponential convergence law sliding mode,RBF neural network sliding mode and second-order sliding mode are analyzed,and the exponential convergence law sliding mode controller is designed by combining the mathematical model of magnetic levitation bearing system,based on which the RBF neural network sliding mode controller and the second-order sliding mode controller are designed respectively.The results are compared with the simulation models in MATLAB/SIMULINK to verify the superiority of the second-order sliding mode method to control the magnetic levitation bearings.Finally,TMS320F28335 is used as the controller to build the rotor experimental platform of the magnetic levitation bearing system,and the displacement sensor is used to collect the rotor’s changing displacement in real time,and the control signal is processed by the power amplifier as the drive of the solenoid coil to realize the stable levitation of the rotor.The exponential convergence law and the second-order sliding mode control experiments are carried out to analyze the displacement variations at different rotational speeds and to compare the control effects of the exponential convergence law and the second-order sliding mode in the magnetic levitation bearing system.