【摘要】 同步磁阻电机参数易受磁饱和、交叉饱和及运行工况变化的影响，因此实现电机参数辨识对提升控制精度有重要意义。针对传统模型参考自适应(model reference adaptive system, MRAS)系统参数辨识方法抗扰动性能差的问题，提出了一种基于主动抗扰控制改进自适应律的模型参考自适应系统参数辨识方法。建立同步旋转坐标系下同步磁阻电机数学模型；构建以定子电流误差为驱动信号的模型参考自适应辨识模型，并基于Popov超稳定性理论设计交轴、直轴电感自适应律，在传统比例积分(proportional-integral, PI)自适应律基础上引入一阶线性主动抗扰控制，以增强参数辨识过程的抗扰能力和动态响应性能；在MATLAB/Simulink平台上结合最大转矩电流比矢量控制系统开展仿真验证。结果表明，所提方法能够实现同步磁阻电机d、q轴电感参数的有效在线辨识，较传统PI型MRAS具有更好的参数跟踪精度。该方法为同步磁阻电机高性能控制提供了可靠的在线参数观测手段。更多还原

【Abstract】 The parameters of synchronous reluctance motor(SynRM) were highly susceptible to magnetic saturation, cross-saturation, and variations in operating conditions; therefore, accurate parameter identification was of great significance for improving control accuracy.An improved model reference adaptive system(MRAS) is developed for SynRM inductance identification, where the conventional proportional-integral(PI)-type adaptive law is augmented with a first-order linear active disturbance rejection controller(ADRC) to strengthen disturbance immunity and transient tracking performance.The d、q-axis SynRM voltage equations are formulated under the synchronous rotating coordinate frame.An MRAS identification model driven by stator current error was constructed, and adaptive laws for the d-axis and q-axis inductances were designed based on Popov’s hyperstability theory.On the basis of the conventional PI adaptive law, a first-order linear ADRC was introduced to enhance the disturbance rejection capability and dynamic response performance of the parameter identification process.Comparative simulations were conducted on a MATLAB/Simulink-based maximum torque per ampere vector control platform.The results demonstrate that the ADRC-enhanced MRAS achieves markedly reduced steady-state oscillation and faster convergence in inductance tracking relative to the conventional PI-based MRAS.This method provides a reliable online parameter observation approach for high-performance control of synchronous reluctance motor.更多还原