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

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

doi:10.1109/tie.2020.3022503

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.

Highlights

N OWADAYS, the ultra-precision motion stages have been widely applied in many nanoscale manufacturing industries like IC manufacturing [1]
In [20], an FD-iterative learning control (ILC) method was proposed for the AFM piezoscanner and experimental results showed that the proposed method can significantly reduce the dynamic coupling errors
To illustrate the proposed frequency-domain data-driven adaptive ILC (FD-AILC) method and evaluate its validity, numerical simulation and experimental test on a wafer stage are implemented

Summary

Introduction

N OWADAYS, the ultra-precision motion stages have been widely applied in many nanoscale manufacturing industries like IC manufacturing [1]. In the control system of the precision motion stages, the feedback control is usually used to suppress the unstructured external disturbance and the system uncertainty, while the feedforward control is used to compensate for the orderly disturbance, such as thrust ripple [4]. The feedforward control is necessary for high-performance motion stages as it can lower the requirements for the feedback control loop [5]. Improvement in feedforward control is a significant step toward meeting higher performance in the generation industrial precision motion stages [6]–[8]

Methods

Results

Conclusion