@inproceedings{886319e6fd354967b0a1ba22f3281fed,
title = "Model Prediction Based Feedforward Control for Precision Motion Stage",
abstract = "In precision motion control, well-designed feedforward control can effectively compensate for the reference tracking error and largely determines the settling time from positioning and acceleration to scanning. The acceleration-snap feedforward method commonly used in wafer stage control can only improve the low-frequency performance of the system. In this paper, a model prediction based feedforward control method is proposed for a nano-scale precision motion platform. The accurate feedforward control input is obtained through the virtual system model. Settling time after positioning and acceleration to scan of the fourthorder trajectory and the tracking error of spiral scan trajectory are greatly reduced, when using a low-order feedback controller. Finally, the effectiveness of this method is proved by experiments.",
keywords = "Feedforward control, Model prediction, Nanometer accuracy, Precision motion stage",
author = "Shuaiqi Chen and Yang Liu and Song, \{Fa Zhi\} and Ning Cui",
note = "Publisher Copyright: {\textcopyright} 2023 Technical Committee on Control Theory, Chinese Association of Automation.; 42nd Chinese Control Conference, CCC 2023 ; Conference date: 24-07-2023 Through 26-07-2023",
year = "2023",
doi = "10.23919/CCC58697.2023.10240384",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "2826--2831",
booktitle = "2023 42nd Chinese Control Conference, CCC 2023",
address = "美国",
}