Precision Synchronous Control of Multiple Motion Systems: A Tube-Based MPC Approach

IF 15.3 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Shuaiqi Chen;Fazhi Song;Yue Dong;Ning Cui;Yang Liu;Xinkai Chen
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引用次数: 0

Abstract

Lithography machines operate in scanning mode for the fabrication of large-scale integrated circuits (ICs), requiring high-precision synchronous motion between the reticle and wafer stages. Disturbances generated by each stage during high-acceleration movements are transmitted through the base frame, resulting in degradation of synchronization performance. To address this challenge, this paper proposes a tube-based model predictive control (tube-MPC) approach for synchronization in lithography machines. First, the proposed modeling method accurately characterizes the coupling disturbances and synchronization dynamics. Subsequently, a tube-MPC approach is developed to ensure that the states of the nominal system are constrained within the terminal constraint set. To reduce the complexity of online computations, an approach is employed to transform online optimization problems into offline problems by creating an online lookup table. This enables the determination of optimal control inputs via a simplified online optimization algorithm. The robustness and trajectory tracking performance of the proposed approach are verified through simulation experiments, demonstrating its effectiveness in enhancing the synchronization performance of multiple motion systems.
多运动系统的精确同步控制:一种基于管的MPC方法
光刻机在扫描模式下工作,用于制造大规模集成电路(ic),需要在光刻线和晶圆级之间进行高精度同步运动。在高加速度运动过程中,各阶段产生的扰动通过基帧传输,导致同步性能下降。为了解决这一挑战,本文提出了一种基于管的模型预测控制(管- mpc)方法,用于光刻机的同步。首先,所提出的建模方法准确表征了耦合扰动和同步动力学。随后,开发了一种管- mpc方法,以确保标称系统的状态在终端约束集内受到约束。为了降低在线计算的复杂性,采用了一种通过创建在线查找表将在线优化问题转化为离线问题的方法。这使得通过简化的在线优化算法确定最优控制输入成为可能。仿真实验验证了该方法的鲁棒性和轨迹跟踪性能,证明了该方法在提高多运动系统同步性能方面的有效性。
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来源期刊
Ieee-Caa Journal of Automatica Sinica
Ieee-Caa Journal of Automatica Sinica Engineering-Control and Systems Engineering
CiteScore
23.50
自引率
11.00%
发文量
880
期刊介绍: The IEEE/CAA Journal of Automatica Sinica is a reputable journal that publishes high-quality papers in English on original theoretical/experimental research and development in the field of automation. The journal covers a wide range of topics including automatic control, artificial intelligence and intelligent control, systems theory and engineering, pattern recognition and intelligent systems, automation engineering and applications, information processing and information systems, network-based automation, robotics, sensing and measurement, and navigation, guidance, and control. Additionally, the journal is abstracted/indexed in several prominent databases including SCIE (Science Citation Index Expanded), EI (Engineering Index), Inspec, Scopus, SCImago, DBLP, CNKI (China National Knowledge Infrastructure), CSCD (Chinese Science Citation Database), and IEEE Xplore.
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