基于互联自适应卡尔曼观测器的PMSM参数辨识  

PMSM parameter identification based on interconnected adaptive Kalman observer

作　　者：李世元 杨恒占[1] 钱富才 谭博[1] Li Shiyuan;Yang Hengzhan;Qian Fucai;Tan Bo(School of Electronic Information Engineering,Xi′an Technological University,Xi′an 710021,China;School of Automation and Information Engineering,Xi′an University of Technology,Xi′an 710048,China)

机构地区：[1]西安工业大学电子信息工程学院,西安710021 [2]西安理工大学自动化与信息工程学院,西安710048

出　　处：《电子测量技术》2024年第24期21-29,共9页Electronic Measurement Technology

基　　金：国家自然科学基金(62073259)项目资助。

摘　　要：针对永磁同步电机运行过程中参数变化及耦合误差问题,本文提出一种基于互联式自适应扩展卡尔曼观测器的在线多参数辨识模型。首先,通过建立互联式多参数耦合补偿辨识模型降低测量噪声和参数耦合误差对辨识精度的影响,获取到高精度的辨识结果。其次,使用自适应方法对扩展卡尔曼观测器进行动态调整,保证工况转变后电机参数辨识的快速性和准确性,并使用Lyapunov函数分析了观测器存在模型误差时的收敛性。最后,在Matlab和RT-LAB半仿真物理系统平台进行了仿真和半仿真实验,结果表明,本文的方法有效降低了测量噪声误差和参数耦合误差,并显著改善了观测器的抗扰动性能。Aiming at the problem of parameter changes and coupling errors during the operation of permanent magnet synchronous motor,this paper proposes an online multi-parameter identification model based on the interconnected adaptive extended Kalman observer.First,by establishing an interconnected multi-parameter coupling compensation identification model to reduce the impact of measurement noise and parameter coupling errors on identification accuracy,high-precision identification results are obtained.Secondly,the adaptive method is used to dynamically adjust the extended Kalman observer to ensure the speed and accuracy of motor parameter identification after working conditions change,and the Lyapunov function is used to analyze the convergence of the observer when there is a model error.Finally,simulation and semi-simulation experiments were conducted on Matlab and RT-LAB semi-simulation physical system platforms.The results show that the method in this paper effectively reduces the measurement noise error and parameter coupling error,and significantly improves the anti-disturbance performance of the observer.

关 键 词：永磁同步电机 互联式观测器 自适应 扩展卡尔曼 在线多参数辨识 

分 类 号：TM351[电气工程—电机] TN751.1[电子电信—电路与系统]