前馈
控制理论(社会学)
扰动(地质)
计算机科学
控制(管理)
阶段(地层学)
过程控制
迭代学习控制
控制工程
工程类
人工智能
生物
过程(计算)
操作系统
古生物学
作者
Mingsheng Cao,Yumeng Bo,Gao Hui-bin
出处
期刊:IEEE Access
[Institute of Electrical and Electronics Engineers]
日期:2020-01-01
卷期号:8: 181224-181232
被引量:4
标识
DOI:10.1109/access.2020.3028379
摘要
This article presents a data-driven algorithm that combines the advantages of iterative feedforward tuning and disturbance rejection control to satisfy the precision requirements and ensure extrapolation capability of wafer scanning. The proposed algorithm differs from pre-existing algorithms in terms of its low requirement of system model, high extrapolation capability for non repetitive trajectory tracking tasks, and high tracking precision. The feedforward controller is tuned based on instrumental variables. It utilizes tracking errors from past iterations to eliminate reference-induced errors without requiring a system model. Meanwhile, the system inverse is approximated during iterative process, and then a disturbance rejection control based on iterative tuning is constructed to compensate for disturbance-induced errors. The proposed algorithm is applied to a wafer stage. The experimental results validate the effectiveness and superiority of the proposed algorithm.
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