This paper presents a data-driven method for waveform optimization of a two-axis smooth impact drive mechanism (SIDM) actuator. The actuator was constructed by two piezoelectric elements (PZTs) perpendicularly fixed to an L-shaped base for two-axis positioning. An XY stage was designed and constructed by assembling the two-axis SIDM actuator. The XY stage could position long motion ranges of several millimeters with nanometer-level resolution, and the size was confined to be 20 mm (X) × 20 mm (Y) × 4.5 mm (H). The data-driven method based on the long short-term memory (LSTM) neural networks was used to predict the optimum input voltage waveform of the actuator. With the optimized input voltage waveform, it was verified that the maximum velocity of the stage could be improved about two times.

中文翻译：

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一种两轴平滑冲击驱动机构执行器的波形优化

本文提出了一种用于两轴平滑冲击驱动机构 (SIDM) 执行器波形优化的数据驱动方法。执行器由两个压电元件 (PZT) 构成，它们垂直固定在 L 形底座上，用于两轴定位。通过组装两轴 SIDM 执行器来设计和构建 XY 平台。XY 平台可以以纳米级分辨率定位几毫米的长运动范围，尺寸限制为 20 mm (X) × 20 mm (Y) × 4.5 mm (H)。基于长短期记忆（LSTM）神经网络的数据驱动方法用于预测执行器的最佳输入电压波形。通过优化的输入电压波形，验证了该阶段的最大速度可以提高约两倍。