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基于自适应陷波滤波器的伺服系统谐振频率估计及抑制
引用本文:龚文全,罗炳章.基于自适应陷波滤波器的伺服系统谐振频率估计及抑制[J].航空动力学报,2019,46(11):37-42, 93.
作者姓名:龚文全  罗炳章
作者单位:广东工业大学 自动化学院,广东 广州511400,广东工业大学 自动化学院,广东 广州511400
摘    要:在使用陷波滤波器抑制伺服系统机械谐振时,需要获取准确的机械谐振频率。为了快速检测出谐振频率,提出了一种基于自适应陷波滤波器(ANF)的机械谐振频率估计算法,通过速度误差信号分析,实现谐振频率在线快速辨识。首先,建立柔性连接伺服系统模型;然后,对ANF频率估计算法进行分析,并且与常用的快速傅里叶变换(FFT)频率检测算法的分析精度和计算速度进行对比。数值比较和仿真验证表明,ANF频率估计算法可以更快地实现谐振频率的精确检测。最后搭建试验平台,以ANF频率估计的结果作为陷波器的中心频率,成功实现了电机转速振荡的抑制,验证了该方法的有效性。

关 键 词:柔性伺服系统    机械谐振抑制    自适应陷波滤波器    频率检测
收稿时间:2019/8/7 0:00:00

Resonance Frequency Estimation and Suppression ofServo System Based on Adaptive Notch Filter
GONG Wenquan and LUO Bingzhang.Resonance Frequency Estimation and Suppression ofServo System Based on Adaptive Notch Filter[J].Journal of Aerospace Power,2019,46(11):37-42, 93.
Authors:GONG Wenquan and LUO Bingzhang
Institution:School of Automation, Guangdong University of Technology, Guangzhou 511400, China and School of Automation, Guangdong University of Technology, Guangzhou 511400, China
Abstract:When using notch filter to suppress mechanical resonance of servo system, it was necessary to obtain accurate mechanical resonance frequency. In order to detect the mechanical resonance frequency quickly, the adaptive notch filter (ANF) frequency estimation strategy for error signal analysis was proposed. Firstly, the mechanical resonance model of flexible connection servo system was established. Secondly, the time consuming and analysis accuracy were compared between the ANF algorithm and fast Fourier transform (FFT). The numerical and the simulation results show that the proposed method is faster than FFT, and resonance frequency can be identified online quickly. Finally, experimental platform was built and the results of ANF frequency estimation were used as the center frequency of the trap. The suppression of motor speed oscillation was successfully realized, and the effectiveness of the algorithm was verified by experiment.
Keywords:flexible servo system  mechanical resonance suppression  adaptive notch filter  frequency detection
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