基于改进自抗扰的永磁轮电机控制

doi:10.19595/j.cnki.1000-6753.tces.250796

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摘要现有磁浮交通使用直线电机存在成本高、控制系统复杂等问题,而Halbach永磁轮（PMEDW）结构简单、工程造价低,能将磁阻力转化为推进力,有望代替直线电机成为一种新型驱动方式。为实现PMEDW推进力调节稳定性及系统快速响应,该文提出一种永磁轮电机的改进自抗扰控制（RAM）策略。首先,对永磁轮电机一体化结构进行优化,加入6 mm硅钢材料,电机磁链幅值提升94.97%;然后,通过实验获取PMEDW在不同转速下的电磁力特性;构建改进永磁轮电机控制系统,相比传统比例-积分（PI）控制,RAM控制响应时间减小约0.5 s,超调量减小约22.4%;最后,建立Simulink与Maxwell的联合仿真模型。结果表明,RAM控制策略能够有效提高永磁轮电机的运行稳定性,为新型永磁轮驱动技术在磁悬浮交通中的应用提供有力支撑。

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	林旺煊
	陈怡浩
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	丁镇涛
	李诤言
	邓自刚

关键词 ：永磁轮电机, 一体化永磁轮, 模型预测控制, 自抗扰控制, 径向基函数神经网络

Abstract：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.

Key words： Permanent magnet electrodynamic wheel motor integrated permanent magnet electrodynamic wheel motor model predictive control active disturbance rejection control radial basis function neural network

收稿日期: 2025-05-13

PACS:

TM351

基金资助:四川省自然科学基金资助项目（2026NSFSCZY0072）

通讯作者: 邓自刚男,1982年生,研究员,博士生导师,研究方向为磁悬浮动力技术及应用。E-mail: deng@swjtu.edu.cn

作者简介: 林旺煊男,2001年生,硕士研究生,研究方向为电机控制。E-mail: wxuan@my.swjtu.edu.cn

引用本文:

林旺煊, 陈怡浩, 石嘉恒, 丁镇涛, 李诤言, 邓自刚. 基于改进自抗扰的永磁轮电机控制[J]. 电工技术学报, 2026, 41(8): 2564-2577. Lin Wangxuan, Chen Yihao, Shi Jiaheng, Ding Zhentao, Li Zhengyan, Deng Zigang. Permanent Magnet Electrodynamic Wheel Motor Based on Improved Active Disturbance Rejection Control. Transactions of China Electrotechnical Society, 2026, 41(8): 2564-2577.

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[1] 张卫华, 邓自刚, 毕海权, 等. 低真空超高速轨道交通研究进展与思考[J]. 机车电传动, 2025(1): 1-13.
Zhang Weihua, Deng Zigang, Bi Haiquan, et al.Research review and reflections on ultra-high-speed rail transit in low-vacuum environments[J]. Electric Drive for Locomotives, 2025(1): 1-13.
[2] Yuan Yuan, Deng Zigang, Zhang Shuai, et al.Working principle and primary electromagnetic characteristics of a permanent magnet electrodynamic wheel for maglev car application[J]. IEEE Transactions on Applied Superconductivity, 2021, 31(8): 1-5.
[3] Lin Peng, Deng Zigang, Ke Zhihao, et al.Dynamic characteristics and working modes of permanent magnet electrodynamic suspension vehicle system based on six wheels of annular halbach structure[J]. Technologies, 2023, 11(1): 16.
[4] 陈怡浩, 梁乐, 刘新, 等. 环形Halbach永磁轮新型充磁设计及磁力特性研究[J]. 机车电传动, 2024(4): 107-117.
Chen Yihao, Liang Le, Liu Xin, et al.Novel design of magnetization and study of magnetic force characteri-stics of annular Halbach permanent magnet electro-dynamic wheel[J]. Electric drive for locomotives, 2024(4): 107-117.
[5] 刘新, 邓自刚, 梁乐, 等. 基于斜置环形Halbach永磁轮的磁浮列车“悬浮-导向-推进”一体化方案设计[J]. 机车电传动, 2023(2): 90-96.
Liu Xin, Deng Zigang, Liang Le, et al.Levitation-guidance-propulsion integrated design for maglev trains based on oblique ring Halbach permanent magnet wheels[J]. Electric Drive for Locomotives, 2023(2): 90-96.
[6] Deng Zigang, Shi Hongfu, Chen Yihao, et al.A cost-effective linear propulsion system featuring PMEDW for HTS maglev vehicle: design, imple-mentation, and dynamic test[J]. Measurement, 2025, 240: 115618.
[7] Kushwaha A, Endla N, Fernandes B G.Motor integrated rotating permanent magnet based electro-dynamic suspension device: part II: investigation of coupled topology[J]. IEEE Transactions on Energy Conversion, 2023, 38(3): 1715-1726.
[8] Park J H, Choi J H, Kim D H, et al.Parametric design of the levitation mechanism for maglev planar trans-portation vehicle[J]. IEEE Transactions on Magnetics, 2004, 40(4): 3069-3071.
[9] Bird J, Lipo T A.Characteristics of an electrodynamic wheel using a 2-D steady-state model[J]. IEEE Transactions on Magnetics, 2007, 43(8): 3395-3405.
[10] 秦伟, 范瑜, 朱熙. 永磁磁轮磁悬浮力的解析与数值方法研究[J]. 微计算机信息, 2010, 26(13): 218-219, 204.
Qin Wei, Fan Yu, Zhu Xi.Levitation force analysis of a permanent magnet wheel[J]. Microcomputer Infor-mation, 2010, 26(13): 218-219, 204.
[11] Paul S, Bird J Z.A 3-D analytic eddy current model for a finite width conductive plate[J]. COMPEL: the International Journal for Computation and Mathe-matics in Electrical and Electronic Engineering, 2013, 33(1/2): 688-706.
[12] Zhang Ze, Deng Zigang, Zhang Shuai, et al.Design and operating mode study of a new concept maglev car employing permanent magnet electrodynamic suspension technology[J]. Sustainability, 2021, 13(11): 5827.
[13] 石秦赓, 朱俊杰, 韩一, 等. 基于自适应滑模观测器的永磁同步电机负载转矩辨识[J]. 电工技术学报, 2025, 40(12): 3868-3882.
Shi Qingeng, Zhu Junjie, Han Yi, et al.Load torque identification of permanent magnet synchronous motor based on adaptive sliding mode observer[J]. Transactions of China Electrotechnical Society, 2025, 40(12): 3868-3882.
[14] 刘忠永, 范涛, 何国林, 等. 高性能永磁同步电机显式模型预测控制算法研究[J]. 电工技术学报, 2023, 38(22): 6039-6058.
Liu Zhongyong, Fan Tao, He Guolin, et al.Research on high-performance explicit model predictive control algorithm for permanent magnet synchronous motors[J]. Transactions of China Electrotechnical Society, 2023, 38(22): 6039-6058.
[15] 赵鑫宇, 王丽梅. 永磁直线同步电机自适应分数阶终端滑模控制[J]. 电工技术学报, 2023, 38(20): 5434-5443.
Zhao Xinyu, Wang Limei.Adaptive fractional-order terminal sliding mode control for permanent magnet linear synchronous motor[J]. Transactions of China Electrotechnical Society, 2023, 38(20): 5434-5443.
[16] Gao Zhiqiang.Scaling and bandwidth-parameterization based controller tuning[C]//Proceedings of the 2003 American Control Conference, Denver, CO, USA, 2003: 4989-4996.
[17] 李思毅, 苏健勇, 杨贵杰. 基于自抗扰控制的永磁同步电机弱磁控制策略[J]. 电工技术学报, 2022, 37(23): 6135-6144.
Li Siyi, Su Jianyong, Yang Guijie.Flux weakening control strategy of permanent magnet synchronous motor based on active disturbance rejection control[J]. Transactions of China Electrotechnical Society, 2022, 37(23): 6135-6144.
[18] 徐奇伟, 龙学汉, 苗轶如, 等. 永磁同步电机双矢量模型预测控制的计算量优化方法研究[J]. 电机与控制学报, 2025, 29(5): 19-30.
Xu Qiwei, Long Xuehan, Miao Yiru, et al.Double-vector model predictive current control for PMSM drive system with low calculation burden[J]. Electric Machines and Control, 2025, 29(5): 19-30.
[19] Moon H T, Kim H S, Youn M J.A discrete-time predictive current control for PMSM[J]. IEEE Transa-ctions on Power Electronics, 2003, 18(1): 464-472.
[20] 邵文强. 基于RBF神经网络的永磁同步电机控制系统[D]. 哈尔滨: 哈尔滨理工大学, 2019.
Shao Wenqiang.Permanent magnet synchronous motor control system based on RBF neural net-work[D]. Harbin: Harbin University of Science and Technology, 2019.
[21] Chen Yihao, Liang Le, Lin Wangxuan, et al.Novel induction plate configuration for permanent magnet electrodynamic wheel systems based on electro-magnetic force optimization and its implementation on HTS system[J]. Physica Scripta, 2025, 100(3): 035512.
[22] 陈卓易, 邱建琪, 金孟加. 永磁同步电机有限集无参数模型预测控制[J]. 电机与控制学报, 2019, 23(1): 19-26.
Chen Zhuoyi, Qiu Jianqi, Jin Mengjia.Finite control set nonparametric model predictive control for permanent magnet synchronous machines[J]. Electric Machines and Control, 2019, 23(1): 19-26.
[23] 闫美洁. 基于模型预测的无位置传感器无刷直流电机控制策略研究[D]. 长春: 吉林大学, 2022.
Yan Meijie.Research on control strategy of sensor-less brushless DC motor based on model predi-ction[D]. Changchun: Jilin University, 2022.
[24] 王建渊, 王海啸, 尹忠刚, 等. 基于一阶线性自抗扰控制器的同步磁阻电机无速度传感器控制[J]. 电工技术学报, 2024, 39(14): 4405-4421.
Wang Jianyuan, Wang Haixiao, Yin Zhonggang, et al.Sensorless control of synchronous reluctance motor based on first order linear active disturbance rejection controller[J]. Transactions of China Electrotechnical Society, 2024, 39(14): 4405-4421.
[25] 陈志旺, 张子振, 曹玉洁. 自抗扰fal函数改进及在四旋翼姿态控制中的应用[J]. 控制与决策, 2018, 33(10): 1901-1907.
Chen Zhiwang, Zhang Zizhen, Cao Yujie.Fal function improvement of ADRC and its application in quadrotor aircraft attitude control[J]. Control and Decision, 2018, 33(10): 1901-1907.
[26] Lozgachev G I.On a method of construction of Lyapunov functions[J]. Automation and Remote Control, 2006, 59: 1365-1369.
[27] 刘志赢, 汪友华, 刘成成, 等. 基于多岛遗传算法与响应面法的横向磁通感应加热装置参数优化设计[J]. 电工技术学报, 2024, 39(10): 3180-3191.
Liu Zhiying, Wang Youhua, Liu Chengcheng, et al.Optimization design of parameters for transverse flux induction heating device based on multi-island genetic algorithm and response surface method[J]. Transactions of China Electrotechnical Society, 2024, 39(10): 3180-3191.