Frequency-Domain Data-Driven Adaptive Iterative Learning Control Approach: With Application to Wafer Stage

Fu, Xuewei; Yang, Xiaofeng; Zanchetta, Pericle; Liu, Yang; Ding, Chenyang; Tang, Mi; Chen, Zhenyu

Abstract

The feedforward control is becoming increasingly important in ultra-precision stages. However, the conventional model-based methods cannot achieve expected performance in new-generation stages since it is hard to obtain the accurate plant model due to the complicated stage dynamical properties. To tackle this problem, this article develops a model-free data-driven adaptive iterative learning approach that is designed in the frequency-domain. Explicitly, the proposed method utilizes the frequency-response data to learn and update the output of the feedforward controller online, which has benefits that both the structure and parameters of the plant model are not required. An unbiased estimation method for the frequency response of the closed-loop system is proposed and proved through the theoretical analysis. Comparative experiments on a linear motor confirm the effectiveness and superiority of the proposed method, and show that it has the ability to avoid the performance deterioration caused by the model mismatch with the increasing iterative trials.

• Journal Article Type: Article
• Acceptance Date: Aug 24, 2020
• Online Publication Date: Sep 15, 2020
• Publication Date: Oct 1, 2021
• Deposit Date: Oct 15, 2021
• Publicly Available Date: Oct 15, 2021
• Journal: IEEE Transactions on Industrial Electronics
• Print ISSN: 0278-0046
• Electronic ISSN: 1557-9948
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 68
• Issue: 10
• Pages: 9309-9318
• DOI: https://doi.org/10.1109/tie.2020.3022503
• Keywords: Electrical and Electronic Engineering; Control and Systems Engineering
• Public URL: https://nottingham-repository.worktribe.com/output/6461102
• Publisher URL: https://ieeexplore.ieee.org/document/9198093
• Additional Information: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.