Data-driven MIMO Fixed-structure Feedforward Control for Ultra-precision Motion Stages of Lithographic Scanners

doi:10.3901/JME.2023.21.099

Abstract

Abstract: The ultra-precision multiple-input multiple-output (MIMO) motion stage is an important mechatronic unit of industrial lithographic scanners for manufacturing integrated circuits, and its excellent tracking performance is the key to ensure the throughput and resolution. An efficient data-driven fixed-structure MIMO feedforward control approach is synthesized for the ultra-precision motion stage to reduce the coupling among multiple degrees of freedom and enhance tracking performance in view of varying references. Specifically, the MIMO feedforward controller is parameterized with the polynomial basis functions. As a result, the inherent stability and robustness against varying references are guaranteed for the MIMO feedforward controller. The Markov parameters of the process sensitivity function matrix are unbiasedly estimated by using impulse response experiment. Then, an efficient data-driven parameter optimization algorithm is developed such that the optimal parameters of the MIMO feedforward controller can be iteratively solved based entirely on the measured data. The proposed approach requires no parametric model of the ultra-precision motion stage, and needs only one tracking experiment in each iteration. The proposed approach is applied to a wafer stage of an industrial lithographic scanner. By tracking 2 different references, the experimental results illustrate that the proposed approach effectively improves the tracking performance and reduces the coupling among the multiple degrees of freedom.

Key words: feedforward control, MIMO, data driven, lithographic scanners, ultra-precision motion stage

CLC Number:

TG156

LI Min, CHEN Taotao, LU Sen, YANG Kaiming, ZHU Yu, HU Chuxiong. Data-driven MIMO Fixed-structure Feedforward Control for Ultra-precision Motion Stages of Lithographic Scanners[J]. Journal of Mechanical Engineering, 2023, 59(21): 99-109.

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