首页|期刊导航|电工技术学报|基于扰动模型前馈与扩张状态观测器复合补偿的直线电机推力波动抑制策略

基于扰动模型前馈与扩张状态观测器复合补偿的直线电机推力波动抑制策略OA

Disturbance Model Feedforward and Extended State Observer Based Composite Compensation Strategy for Thrust Fluctuation Suppression in Linear Motor

中文摘要英文摘要

针对高精度永磁同步直线电机(PMLSM)的磁阻力、摩擦力等推力波动问题,该文设计了一种基于扰动模型前馈(DMF)与线性扩张状态观测器(LESO)相结合的推力波动复合补偿策略.首先,从 PMLSM 的物理结构及磁场分布特点,分析了电机动子在运动过程中的受力情况和推力波动的位置、频率特性.发现在高速高动态响应下推力波动存在较高的频率分量,会导致系统伺服误差变大,因此提出扰动建模与 LESO 相结合的推力波动复合补偿策略.其次,使用神经网络对磁阻力进行位置域建模,使用分段线性模型对摩擦力进行速度域建模,使用 LESO对建模后残余的扰动进一步估计并补偿,以提高系统在全速域下的推力波动抑制能力.最后,通过 PMLSM 样机平台的位置、速度伺服试验分析了所提策略对磁阻力各频率分量补偿的有效性,验证了所提策略对推力波动的抑制能力以及对电机动子质量参数变化的适应性.结果表明,该文所提控制策略在稳态、动态下均具有良好的推力波动补偿效果,能够提高 PMLSM 系统伺服控制精度,并对电机动子质量变化具有良好的鲁棒性.

An AC permanent-magnet synchronous linear motor(PMLSM)offers high response speed and control accuracy and is widely used in high-precision manufacturing applications.However,due to its unique physical structure,PMLSM is inevitably affected by thrust fluctuations,including detent and friction forces during movement,which deteriorate the motor's control performance.To address thrust fluctuation problems in high-precision PMLSM,a composite compensation strategy is designed that combines disturbance model feedforward(DMF)and a linear extended state observer(LESO). Firstly,based on the physical structure and magnetic field distribution of the PMLSM,the force of the motor mover during motion,along with its position and frequency characteristics of thrust fluctuation,are analyzed.It is found that a high-frequency component of thrust fluctuation occurs at high speed and high dynamic response,leading to an increase in servo error.Therefore,a thrust-fluctuation composite compensation strategy is proposed.Secondly,a neural network is used to model the detent force in the position domain,a piecewise linear friction model is used to model the friction force in the velocity domain,and the residual disturbance after modeling is further estimated and compensated by LESO.In addition,to enhance the tracking performance of the instructions,a two-degree-of-freedom control structure combining differential feedforward and PI control is adopted.Considering the real-time requirement of the servo system,the computational amount of the proposed thrust fluctuation composite compensation strategy is also analyzed. Finally,the effectiveness of the proposed strategy is evaluated through position and velocity-servo experiments on a PMLSM prototype platform.Trapezoidal-wave-position servo experiments verify the proposed strategy for thrust fluctuation suppression.Additionally,experiments conducted at different speeds confirm that the proposed strategy suppresses thrust fluctuations across the full frequency range.Furthermore,sinusoidal position experiments show that the proposed control strategy provides adequate thrust fluctuation compensation in both steady-state and dynamic conditions,improving the servo performance of the PMLSM system and meeting the real-time computing requirement.The suppression rate of thrust fluctuations reaches 87.39%,with a steady-state position control accuracy of 2.72 μm and a speed control accuracy of 4.46 mm/min at 4 m/min.In addition,the strategy is robust to the mass change in the motor mover.

李叶松;卢玉清

华中科技大学人工智能与自动化学院 武汉 430074华中科技大学人工智能与自动化学院 武汉 430074

信息技术与安全科学

永磁同步直线电机推力波动神经网络建模扩张状态观测器

Permanent magnet linear synchronous motorthrust fluctuationneural network modelingextended state observer

《电工技术学报》 2026 (8)

2590-2600,11

10.19595/j.cnki.1000-6753.tces.250792

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