Wafer Stage Modal Model Identification by Modified Vector Fitting Method

被引:0
作者
Yang X. [1 ,2 ]
Zhang M. [1 ,2 ]
Cheng R. [1 ,2 ]
Zhu Y. [1 ,2 ]
Wang L. [1 ,2 ]
机构
[1] State Key Laboratory of Tribology, Department of Mechanical Engineering, Tsinghua University, Beijing
[2] Beijing Key Laboratory of Precision, Ultra-precision Manufacturing Equipments and Control, Tsinghua University, Beijing
来源
Journal of Beijing Institute of Technology (English Edition) | 2021年 / 30卷
基金
中国国家自然科学基金;
关键词
System identification; Vector fitting; Wafer stage;
D O I
10.15918/j.jbit1004-0579.20052
中图分类号
学科分类号
摘要
Vector fitting is modified in this study for the parametric identification of a model with an undamped rigid body mode in the frequency domain. The modal model of a six-degree-of-freedom (6DOF) wafer stage is identified using the modified vector fitting method. The modal model is typically fitted from the matrix fraction description (MFD) form of the transfer function, which increases the cost function. The vector fitting in frequency domain provides an approach to fitting the modal model directly from frequency response functions(FRFs) via a partial rational basis function, the poles of which can be obtained by pole relocation technology. The traditional vector fitting method is not applicable in identifying systems containing rigid body modes. The method is reformulated here and effectively applied for wafer stage identification. The accuracy of the fitted model is validated by control loop simulation. © 2020 Journal of Beijing Institute of Technology
引用
收藏
页码:187 / 195
页数:8
相关论文
共 21 条
[1]  
Butler H., Position control in lithographic equipment: An enabler for current-day chip manufacturing [J], IEEE Control Systems Magazine, 31, 5, pp. 28-47, (2011)
[2]  
Oomen T., Advanced motion control for precision mechatronics: Control, identification, and learning of complex systems [J], IEEJ Journal of Industry Applications, 7, 2, (2018)
[3]  
Bruijnen D, Dijk N V., Combined input shaping and feedforward control for flexible motion systems, Proceedings of the American Control Conference, (2012)
[4]  
Butterworth J A, Pao L Y, Abramovitch D Y., Analysis and comparison of three discrete-time feedforward model-inverse control techniques for nonminimum-phase systems [J], Mechatronics, 22, 5, pp. 577-587, (2012)
[5]  
Heertjes M, Hennekens D, Engelen A V, Et al., Dynamic decoupling in motion systems using a gradient approximation-based algorithm, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, pp. 5086-5091, (2009)
[6]  
Herpen R V, Oomen T, Kikken E, Et al., Exploiting additional actuators and sensors for nano-positioning robust motion control, Proceedings of 2014 American Control Conference, pp. 984-990, (2014)
[7]  
Oomen T, Grassens E, Hendriks F., Inferential motion control: Identification and robust control framework for positioning an unmeasurable point of interest [J], IEEE Transactions on Control Systems Technology, 23, 4, pp. 1602-1610, (2015)
[8]  
Dorosti M, Fey R, Heertjes M, Et al., Finite element model reduction and model updating of structures for control [J], IFAC Proceedings Volumes, 47, 3, pp. 4517-4522, (2014)
[9]  
Balas G J, Doyle J C., Identification of flexible structures for robust control [J], IEEE Control Systems Magazine, 10, 4, pp. 51-58, (1990)
[10]  
Pintelon R, Guillaume P, Rolain Y, Et al., Parametric identification of transfer functions in the frequency domain: A survey [J], IEEE Transactions on Automatic Control, 39, 11, pp. 2245-2260, (1994)