基于改进Preisach模型的音圈电机复杂迟滞建模

党选举;梁卫;姜辉

振动与冲击 ›› 2012, Vol. 31 ›› Issue (21) : 156-162.

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PDF(2363 KB)
振动与冲击 ›› 2012, Vol. 31 ›› Issue (21) : 156-162.
论文

基于改进Preisach模型的音圈电机复杂迟滞建模

  • 党选举,梁卫,姜辉
作者信息 +

Modeling of Complex Hysteresis for Voice Coil Motor Based on Improved Preisach Model

  • DANG Xuanju, LIANG Wei, JIANG Hui
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文章历史 +

摘要

针对音圈电机在高频响、高速、高加速度运动时存在的一种特殊复杂迟滞特性,提出一种改进的Preisach迟滞与RBF神经网络相结合的动态迟滞混合模型。采用逐次逼近的思想,第一级通过构造一个改进型Preisach模型,引入非单调信息,使其输出具有非单调迟滞特性。第二级采用动态RBF神经网络对第一级输出的相位和幅值进行补偿,实现对音圈电机实际输出的高精度逼近。基于实测数据的仿真实验结果表明,所提模型对一般迟滞和非单调复杂迟滞的建模都是有效的。与动态神经网络建模相比,具有更高的模型精度。

Abstract

A special complex hysteresis characteristic exists in Voice Coil Motor (VCM) under high-frequency, high-speed and high-acceleration, which makes the system performance go worse. In order to achieve the precise positioning control for VCM, a hybrid hysteresis model which consists of the improved Preisach units and dynamic neural network was proposed. In the improved Preisach model, the non-monotonic information was introduced for describing the non-monotonic hysteresis behavior. Based on the former part, a dynamic radial basis function (RBF) neural network was applied to compensate the amplitude and phase error between the dynamic Preisach output and the real VCM hysteresis for a higher accuracy. Finally, the simulation experimental results based on the measured data show that the proposed hybrid model is effective not only for the general hysteresis modeling and but also for the non-monotonic complex hysteresis. Comparing with the dynamic neural network modeling, this hybrid model is of a higher modeling accuracy.

关键词

音圈电机 / 复杂迟滞 / 改进Preisach模型 / 非单调 / RBF神经网络

Key words

voice coil motor actuator / complex hysteresis / modified Preisach model / non-monotonic function / RBF neuron network

引用本文

导出引用
党选举;梁卫;姜辉. 基于改进Preisach模型的音圈电机复杂迟滞建模[J]. 振动与冲击, 2012, 31(21): 156-162
DANG Xuanju;LIANG Wei;JIANG Hui. Modeling of Complex Hysteresis for Voice Coil Motor Based on Improved Preisach Model[J]. Journal of Vibration and Shock, 2012, 31(21): 156-162

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