基于自抗扰迭代学习控制的开关磁阻电机转矩脉动抑制

Active disturbance rejection based iterative learning control for torque ripple suppression in SRM

中文关键词  开关磁阻电机  转矩脉动  转矩分配  自抗扰迭代学习控制  转矩控制

英文关键词  switched reluctance motor  torque ripple  torque distribution  iterative learning control based on ADRC

中文摘要

      针对开关磁阻电机双凸极结构和磁路饱和非线性导致开关磁阻电机转矩脉动大的问题, 本文基于一种新 型的数据驱动控制方法——自抗扰迭代学习控制, 将开关磁阻电机看成是空间重复运动对象, 设计空间迭代域补偿 机制用于抑制电机非线性特性所带来的换相转矩脉动. 提出了基于空间域扩张状态扰动补偿机制的转矩分配控制 策略, 在无法精确获取电机非线性模型的情形下, 设计了非线性转矩补偿器和电流控制器对各相电流进行精确补偿 和精确跟踪控制. 仿真研究表明, 基于自抗扰迭代学习的控制策略能显著快速地抑制开关磁阻电机的转矩脉动, 可 望在开关磁阻电机的实际应用中发挥作用.

英文摘要

      To minimize the torque ripple caused by the nonlinear characteristics, this paper regards switched reluctance motor as the spatial repetitive motion object, and then designs a current and torque compensation mechanism based on active disturbance rejection based iterative learning control (ADR-ILC), which is a novel data-driven control strategy. The torque sharing function is used to distribute the given torque to each phase, and a non-linear torque compensator based on ADR-ILC is added to the ”torque-current” conversion module to compensate for nonlinear error, which can accurately complete the ”torque-current” conversion without accurately knowing the motor model. Similarly,current tracking is achieved accurately by applying ADR-ILC controller. Simulation shows that the control strategy based on ADR-ILC can suppress torque ripple significantly and quickly, which is expected to play a role in the practical application.