考虑测量噪声的朗道自适应惯量辨识方法

传统朗道自适应惯量辨识方法只有一个自适应系数可以调节,难以同时兼顾辨识速度和辨识精度,导致速度自适应控制系统在测量噪声较大的情况下容易不稳定。为解决这一问题,提出了一种考虑测量噪声的朗道自适应惯量辨识方法。该方法采用相同的低通滤波器对速度和电磁转矩同时进行滤波,保证了辨识模型与无滤波时的相同。在此基础上综合调节自适应系数和滤波器时间常数,在保证辨识速度的前提下减小辨识系统的噪声,提高辨识精度,从而提高了速度自适应控制系统的稳定性。仿真和试验验证了所提方法的正确性和有效性。

Landau Adaptive Inertia Identification Method ConsideringMeasurement Noise

Due to the fact that only one adaptive coefficient could be adjusted in traditional Landau method for inertia identification, it was difficult to obtain both good identification speed and identification accuracy, leading to the instability of the speed adaptive control system in the case of large measurement noise. To solve this problem, a Landau method for inertia identification considering measurement noise was proposed. By using the same lowpass filter for both the speed and the electromagnetic torque, the reference model was the same as the one without filter. On this basis, both the adaptive coefficient and the time constant of the filter were adjusted for the same identification speed while with better noise suppression, so as to improve the inertia identification accuracy and the stability of the speed adaptive control system. The correctness and effectiveness of the proposed method were verified by simulations and experiments.