公开(公告)号：WO2019076525A1

公开(公告)日：2019-04-25

申请号：PCT/EP2018/073792

申请日：2018-09-05

Applicant: ASML NETHERLANDS B.V.

Inventor： BOLDER, Joost, Johan ,  HEIJMANS, Peter, Michel, Silvester, Maria ,  VAN DUIVENBODE, Jeroen ,  VRENKEN, Ruud, Hubertus, Silvester

IPC: G03F7/20 ,  H02K41/03 ,  H02K41/035 ,  H02P6/00 ,  H02K3/28 ,  G05B19/416

Abstract: The invention relates to a motor (LD) comprising: • a stationary part (STP), comprising: • a row of coil assemblies (UCA,LCA), the coil assemblies having multiple phases, • a movable part (MP), comprising: • a row of permanent magnets (UPM,LPM), wherein the row of coil assemblies has a first length and the row of permanent magnets has a second length, wherein the second length is smaller than the first length, wherein the coil assemblies are arranged to interact with permanent magnets aligned with the coil assemblies to generate a driving force, • a comparator to compare a position measurement signal representative for an actual position of the movable part with a set- point signal representative for a desired position of the movable part to provide an error signal; • a motion feedback controller configured to provide a control signal on the basis of the error signal; at least one current amplifier configured to provide an actuation signal to the coil assemblies on the basis of the control signal, • wherein the motor comprises a feedforward device, wherein the feedforward device is configured to provide a current amplifier feedforward signal on the basis of the set-point signal, or a derivative thereof, wherein the current amplifier feedforward signal is provided to the at least one current amplifier to compensate for unbalanced back electromotive forces on one or more of the coil assemblies due to the one or more coil assemblies being only partly aligned with the permanent magnets.

公开(公告)号：WO2022008198A1

公开(公告)日：2022-01-13

申请号：PCT/EP2021/066479

申请日：2021-06-17

Applicant: ASML NETHERLANDS B.V.

Inventor： VAN BERKEL, Koos ,  BOLDER, Joost, Johan ,  BOSMA, Stijn

IPC: G03F7/20 ,  G05B13/02 ,  G05B13/04 ,  G06N3/02 ,  G06N3/08 ,  G06N20/00

Abstract: Variable setpoints and/or other factors may limit iterative learning control for moving components of an apparatus. The present disclosure describes a processor configured to control movement of a component (ST) of an apparatus with at least one prescribed movement. The processor is configured to receive a control input (SP) such as and/or including a variable setpoint. The control input indicates the at least one prescribed movement for the component. The processor is configured to determine, with a trained artificial neural network (PM), based on the control input (SP), a control output for the component (ST). The artificial neural network is trained with training data such that the artificial neural network determines the control output regardless of whether or not the control input falls outside the training data. The processor controls the component based on at least the control output.

公开(公告)号：WO2022008174A1

公开(公告)日：2022-01-13

申请号：PCT/EP2021/065947

申请日：2021-06-14

Applicant: ASML NETHERLANDS B.V.

Inventor： GUO, Chaoqun ,  KHEDEKAR, Satej, Subhash ,  GANTAPARA, Anjan Prasad ,  LIN, Chenxi ,  CASTELIJNS, Henricus, Jozef ,  CHEN, Hongwei ,  BOND, Stephen Henry ,  LI, Zhaoze ,  MOSSAVAT, Seyed Iman ,  ZOU, Yi ,  YPMA, Alexander ,  ZHANG, Youping ,  DICKER, Gerald ,  STEINMEIER, Ewout, Klaas ,  VAN BERKEL, Koos ,  BOLDER, Joost, Johan ,  HUBAUX, Arnaud ,  HLOD, Andriy, Vasyliovich ,  GONZALEZ HUESCA, Juan Manuel ,  AARDEN, Frans Bernard

IPC: G03F7/20

Abstract: Generating a control output for a patterning process is described. A control input is received. The control input is for controlling the patterning process. The control input comprises one or more parameters used in the patterning process. The control output is generated with a trained machine learning model based on the control input. The machine learning model is trained with training data generated from simulation of the patterning process and/or actual process data. The training data comprises 1) a plurality of training control inputs corresponding to a plurality of operational conditions of the patterning process, where the plurality of operational conditions of the patterning process are associated with operational condition specific behavior of the patterning process over time, and 2) training control outputs generated using a physical model based on the training control inputs.