摘要
为了削弱模型参考自适应法在辨识时变参数时出现的波动,在模型参考自适应算法的基础上,引入辨识结果的反馈,辨识结果未稳定时选择较大的自适应增益,能较快的辨识参数,辨识结果稳定后,选择较小的自适应增益,避免参数变化时辨识结果的波动。将该方法用于永磁同步电机转动惯量的辨识仿真实验表明:该方法削弱了原辨识算法在辨识时变参数时的波动,能更快地跟踪转动惯量的变化,表现出更好的辨识特性。
When model reference self-adaptive algorithm is used to identify the variable parameter, the identification result is fluctuant. To reduce the fluctuation,on the basis of model reference self-adaptive algorithm, added feedback of the identification. In the process of the identification, choose the larger adaptive gain to identify the parameter quickly; when the result of identification is steady, choose the smaller adaptive gain to reduce the fluctuation. Apply the improved identification algorithms to identify PMSM moment of inertia, the simulation and experiments show that the improved algorithms are free from the fluctuation, the identifications are more quickly and high precision.
出处
《电气传动》
北大核心
2009年第5期47-50,共4页
Electric Drive
基金
江苏省自然科学基金(BK2007540)
关键词
参数辨识
永磁同步电机
模型参考自适应
转动惯量
parameter identification
permanent magnet synchronous motor （PMSM）
model referenceself-adaptive
moment of inertia
