基于迭代学习控制的超低频标准振动谐波抑制

Wei Li, Junning Cui, Limin Zou
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引用次数: 0

摘要

电磁标准激振器产生的最大加速度幅值受冲程限制,随振动频率降低约12 dB/Oct,因此超低频振动的标定具有重要的意义和难度。因此,信噪比相应降低,超低频标准振动的谐波失真成为一个亟待解决的难题。提出了一种基于迭代学习的谐波抑制方法。研究了ULF标准激振器的系统特性,提出了一种基于位移反馈的PD型迭代学习控制方法,通过PD控制消除扰动,通过迭代学习抑制重复扰动矩,从而有效提高了ULF标准振动波形的信噪比和精度。仿真结果表明,该方法能有效降低系统的跟踪误差,经过4次迭代后,加速度波形的谐波失真从1%降低到0.03%。
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Harmonic Suppression of Ultralow-frequency Standard Vibration based on Iterative Learning Control
Calibration of ultra-low frequency (ULF) vibration is of great significance and degree of difficulty, because the maximum amplitude of acceleration produced by electromagnetic standard vibration exciters is limited by stroke and decreases with vibration frequency by 12 dB/Oct. Therefore, the signal to noise ratio decreases correspondingly and harmonic distortion of ULF standard vibration becomes a challenging problem to be solved. A harmonic suppression method based on iterative learning is proposed in this paper. The system characteristics of ULF standard vibration exciters are studied, a PD-type iterative learning control method based on displacement feedback is introduced to eliminate disturbances by PD control and suppress repetitive disturbance moments by iterative learning, thus to effectively improve the signal-to-noise ratio and accuracy of ULF standard vibration waveforms. Simulation results show that this method can effectively reduce the tracking error of the system, and harmonic distortion of acceleration waveform is reduced from 1% to 0.03% after four times of iteration.
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