基于改进自抗扰的永磁轮电机控制OA

With the development of maglev transportation technology,the existing high-temperature superconducting maglev trains that use a long-stator linear motor as the driving system face high costs,complex structures,and complex control systems.The Halbach Permanent Magnet Electrodynamic Wheel(PM EDW)has a simple structure and low engineering cost.It can convert magnetic resistance into propulsion force and is expected to replace linear motors.The working principle of PM EDW is to drive rotation.The interaction between the rotating magnetic field generated by the PM EDW and the conductor plate eventually produces the electromagnetic force.In this paper,PM EDW and drive motor structures are coupled to construct the PM EDW motor.However,the PM EDW motor drive system is a strongly coupled,nonlinear,and multi-variable system.Therefore,this paper proposes an improved active disturbance rejection control(ADRC)strategy based on model predictive control(MPC)to rapidly control the propulsion force and improve the system's anti-interference ability and stability. Firstly,the PM EDW motor structure is optimized by introducing a 6 mm-thick silicon steel sheet between the Halbach permanent magnet array and the conventional NS pole permanent magnet.This action significantly concentrates the flux path,reduces the flux leakage,and increases the flux density at the air gap.The simulation results show that the optimized design increases the amplitude of the three-phase flux linkage by about 94.97%,improving the magnetic field utilization and electromagnetic torque. Secondly,to obtain the electromagnetic characteristics of the PM EDW motor under actual operation,the propulsion and guiding forces at different speeds were measured using the PM EDW motor's electromagnetic force test platform.The accuracy of the theoretical model is verified by comparing measured electromagnetic force data with Maxwell finite-element simulation results.A nonlinear fitting relationship between the propulsion force and the speed is obtained,providing support for control system modeling. In terms of control system design,this paper proposes a hybrid control strategy of improved ADRC and MPC,referred to as RAM controller(RBF-ADRC-MPC,RAM).Among them,the current inner loop uses MPC to achieve high-precision adjustment,avoiding the overshoot and oscillation problems of traditional PI control.The improved ADRC is used in the outer loop control to enhance the system response speed and interference suppression.To address the cumbersome problem of ADRC parameter tuning,the RAM controller introduces an RBF neural network to dynamically adjust the parameters β1 and β2 online,thereby enabling self-tuning and enhancing the control system's adaptability to environmental changes. Compared with PI control,RAM control reduces response time by about 0.5 s,reduces the overshoot by about 22.4%,and demonstrates stronger anti-interference ability under load changes.The effectiveness of RAM control is verified by co-simulation. The proposed RAM control strategy can achieve rapid and accurate control of the propulsion force and exhibits strong anti-interference,making it suitable for the magnetic wheel drive system of the high-temperature superconducting pin maglev train.It provides a reference and helps with the design of a new maglev train driving mode,an eddy current brake,and a non-contact conveyor plate in the future.