Acceleration waveform reproduction control of hypergravity centrifugal shaking table based on data driven iterative learning control and two-degree-of-freedom control.

Zhu Yang, Haibo Xie
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Abstract

The hypergravity centrifugal shaking table (HCST) is the most effective means for studying the disaster effects of rock and soil earthquakes, and the accurate control of acceleration waveform recurrence is the critical problem. This paper compares the dynamic characteristics of the normal gravity shaking table (NGST) and the HCST, highlighting the latter's particularities, and analyzes the limitations of the existing control strategy. Meanwhile, a hypergravity unidirectional airborne shaking table (HUAST) is designed, and a data-driven iterative learning control and two-degree-of-freedom control-based acceleration waveform reproduction strategy is proposed and experimentally verified.

基于数据驱动迭代学习控制和两自由度控制的超重力离心振动台加速度波形再现控制。
超重力离心振动台(HCST)是研究岩土地震灾害效应的最有效手段,而加速度波形重现的精确控制是关键问题。本文比较了正常重力振动台(NGST)和超重力离心振动台(HCST)的动态特性,强调了后者的特殊性,并分析了现有控制策略的局限性。同时,设计了超重力单向机载振动台(HUAST),提出了基于数据驱动的迭代学习控制和两自由度控制的加速度波形重现策略,并进行了实验验证。
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