Control apparatus, imprint apparatus, and method of manufacturing article

Patent metadata

Field	Value
Publication number	US-2022063176-A1
Application number	US-202117410191-A
Country	US
Kind code	A1
Filing date	Aug 24, 2021
Priority date	Aug 28, 2020
Publication date	Mar 3, 2022
Grant date	—

Abstract

A control apparatus which controls a force applied to an object, includes a driver configured to apply the force to the object, an estimator configured to estimate, based on information related to a state of the object, an estimated value of a disturbance force to be applied to the object, a corrector configured to correct, based on the estimated value, a command value provided to the driver so as to reduce an influence of the disturbance force, and a determiner configured to execute processing for determining a plurality of parameter values to be used by the estimator to obtain the estimated value based on the information.

First claim

What is claimed is:

1 . A control apparatus that controls a force applied to an object, comprising:
a driver configured to apply the force to the object; an estimator configured to estimate, based on information related to a state of the object, an estimated value of a disturbance force to be applied to the object; a corrector configured to correct, based on the estimated value, a command value provided to the driver so as to reduce an influence of the disturbance force; and a determiner configured to execute processing for determining a plurality of parameter values to be used by the estimator to obtain the estimated value based on the information.

2 . The apparatus according to claim 1 , wherein the disturbance force is applied to the object via a member which is directly connected or indirectly connected to the object.

3 . The apparatus according to claim 2 , wherein the plurality of parameter values include a parameter value which indicates an attenuation and a stiffness of the member.

4 . The apparatus according to claim 1 , further comprising:
a measurement unit configured to measure the information.

5 . The apparatus according to claim 1 , further comprising:
an acquirer configured to acquire the disturbance force, wherein the determiner determines, based on the disturbance force acquired by the acquirer, the plurality of parameter values through machine learning.

6 . The apparatus according to claim 5 , wherein in position feedback control in which the driver is operated based on a difference between a position command value for commanding a position of the object and a measured value of the position of the object so that the position command value and the measured value will match, the acquirer acquires the disturbance force based on the difference and the measured value.

7 . The apparatus according to claim 5 , wherein the machine learning is unsupervised learning.

8 . The apparatus according to claim 7 , wherein in the unsupervised learning, one of a mean squared error, an average mean squared error, a mean absolute error, and a mean squared logarithmic error is used as a loss function.

9 . The apparatus according to claim 5 , wherein the machine learning is reinforcement learning.

10 . The apparatus according to claim 9 , wherein in the reinforcement learning, a reciprocal of one of a mean squared error, an average mean squared error, a mean absolute error, and a mean squared logarithmic error is used as a reward.

11 . The apparatus according to claim 1 , wherein the apparatus is incorporated in an imprint apparatus configured to bring a mold into contact with an imprint material on a substrate and to cure the imprint material to form a pattern made of a cured product of the imprint material.

12 . The apparatus according to claim 11 , wherein a force applied to a mold holder configured to hold the mold is controlled as the force to be applied to the object.

13 . An imprint apparatus that brings a mold into contact with an imprint material on a substrate and cures the imprint material to form a pattern made of a cured product of the imprint material, comprising:
a mold holder configured to hold the mold; a driver configured to apply a force to the mold holder; an estimator configured to estimate, based on information related to a state of the mold holder, an estimated value of a disturbance force to be applied to the mold holder; a corrector configured to correct, based on the estimated value, a command value provided to the driver so as to reduce an influence of the disturbance force; and a determiner configured to execute processing for determining a plurality of parameter values to be used by the estimator to obtain the estimated value based on the information.

14 . The apparatus according to claim 13 , wherein the disturbance force is applied to the mold holder via a member which is directly connected or indirectly connected to the mold holder.

15 . The apparatus according to claim 14 , wherein the plurality of parameter values include a parameter value which indicates an attenuation and a stiffness of the member.

16 . The apparatus according to claim 13 , further comprising:
a measurement unit configured to measure the information.

17 . The apparatus according to claim 13 , further comprising:
an acquirer configured to acquire the disturbance force, wherein the determiner determines, based on the disturbance force acquired by the acquirer, the plurality of parameter values through machine learning.

18 . The apparatus according to claim 17 , wherein in position feedback control in which the driver is operated based on a difference between a position command value for commanding a position of the object and a measured value of the position of the object so that the position command value and the measured value will match, the acquirer acquires the disturbance force based on the difference and the measured value.

19 . A method of manufacturing an article, comprising:
forming a pattern on a substrate by using an imprint apparatus defined in claim 13 ; and processing the substrate on which the pattern is formed in the forming.

Assignees

• Canon Kk

Inventors

• Nawata Ryo
• Sekiguchi Hiroyuki
• Shibayama Takashi
• Onizawa Yuma

Classifications

• H10P74/23

  characterised by multiple measurements, corrections, marking or sorting processes · CPC title

• G05B19/404

  characterised by control arrangements for compensation, e.g. for backlash, overshoot, tool offset, tool wear, temperature, machine construction errors, load, inertia (G05B19/19, G05B19/41 take precedence) · CPC title

• G06N20/00

  Machine learning · CPC title

• G03F7/0002 Primary

  Lithographic processes using patterning methods other than those involving the exposure to radiation, e.g. by stamping · CPC title

• B29C59/02

  by mechanical means, e.g. pressing {(B29C59/007 takes precedence; embossing expanded porous articles B29C44/5627)} · CPC title