Abstract Thermally induced deformations are becoming increasingly important for the control performance of precision motion systems. The aim of this paper is to identify the underlying thermal dynamics in view of precision motion control. Identifying thermal systems is challenging due to strong transients, large time constants, excitation signal limitations, large environmental disturbances, and temperature dependent behavior. An approach for non-parametric identification is developed that is particularly suitable for thermal aspects in mechatronic systems. In particular (1) reduced experiment time is achieved by utilizing transient data in the identification procedure. (2) an approach is presented that exploits measured ambient air temperature fluctuations as additional inputs to the identification setup. (3) the non-parametric model, obtained through (1) and (2), is used as a basis for parameter estimation of a grey-box parametric model. The presented methods form a complete framework that facilitates the implementation of advanced control techniques and error compensation strategies by providing high-fidelity models, enabling increased accuracy and throughput in high precision motion control.

中文翻译：

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快速准确地识别用于精密运动控制的热动力学：利用瞬态数据和额外的干扰输入

摘要 热致变形对于精密运动系统的控制性能变得越来越重要。本文的目的是从精确运动控制的角度确定潜在的热动力学。由于强瞬变、大时间常数、激励信号限制、大环境干扰和温度相关行为，识别热系统具有挑战性。开发了一种非参数识别方法，特别适用于机电系统中的热方面。特别是 (1) 通过在识别过程中利用瞬态数据来减少实验时间。(2) 提出了一种方法，该方法利用测量的环境空气温度波动作为识别设置的附加输入。(3) 非参数模型，通过（1）和（2）得到的，被用作灰盒参数模型的参数估计的基础。所提出的方法形成了一个完整的框架，通过提供高保真模型来促进先进控制技术和误差补偿策略的实施，从而提高高精度运动控制的准确性和吞吐量。