Multi-layer spatial iterative learning control for micro-additive manufacturing

Leontine Aarnoudse; Christopher Pannier; Zahra Afkhami; Tom Oomen; Kira Barton

doi:10.1016/j.ifacol.2019.11.657

Multi-layer spatial iterative learning control for micro-additive manufacturing

Leontine Aarnoudse, Christopher Pannier, Zahra Afkhami, Tom Oomen, Kira Barton

Research output: Contribution to journal › Conference article › Academic › peer-review

5 Citations (Scopus)

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Abstract

Spatial iterative learning control (SILC) has been used in the control of additive manufacturing systems that can be described by their spatial dynamics. Since the current framework is limited to single-layer parts, the aim of this paper is to provide an approach to multi-layer SILC using learning in the layer-to-layer dimension. Mathematical formulation of a multi-layer SILC controller is provided, and active feedback control is demonstrated to reduce the error accumulation over the iterations. Simulation results using a model of high-resolution e-jet printing verify performance improvements for the proposed framework.

Original language	English
Pages (from-to)	97-102
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	52
Issue number	15
DOIs	https://doi.org/10.1016/j.ifacol.2019.11.657
Publication status	Published - Sep 2019
Event	8th IFAC Symposium on Mechatronic Systems (MECHATRONICS 2019), and 11th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2019) Vienna, Austria - Vienna, Austria Duration: 4 Sep 2019 → 6 Sep 2019 http://www.mechatronicsnolcos2019.org/

Keywords

Control applications
Feedback control
Learning control
Micro-additive manufacturing
Spatial domain
Feedback Control
Micro-Additive Manufacturing
Control Applications
Spatial Domain
Learning Control

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title = "Multi-layer spatial iterative learning control for micro-additive manufacturing",

abstract = "Spatial iterative learning control (SILC) has been used in the control of additive manufacturing systems that can be described by their spatial dynamics. Since the current framework is limited to single-layer parts, the aim of this paper is to provide an approach to multi-layer SILC using learning in the layer-to-layer dimension. Mathematical formulation of a multi-layer SILC controller is provided, and active feedback control is demonstrated to reduce the error accumulation over the iterations. Simulation results using a model of high-resolution e-jet printing verify performance improvements for the proposed framework.",

keywords = "Control applications, Feedback control, Learning control, Micro-additive manufacturing, Spatial domain, Feedback Control, Micro-Additive Manufacturing, Control Applications, Spatial Domain, Learning Control",

author = "Leontine Aarnoudse and Christopher Pannier and Zahra Afkhami and Tom Oomen and Kira Barton",

year = "2019",

month = sep,

doi = "10.1016/j.ifacol.2019.11.657",

language = "English",

volume = "52",

pages = "97--102",

journal = "IFAC-PapersOnLine",

issn = "2405-8963",

publisher = "Elsevier",

number = "15",

note = "8th IFAC Symposium on Mechatronic Systems (MECHATRONICS 2019), and 11th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2019) Vienna, Austria ; Conference date: 04-09-2019 Through 06-09-2019",

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T1 - Multi-layer spatial iterative learning control for micro-additive manufacturing

AU - Aarnoudse, Leontine

AU - Pannier, Christopher

AU - Afkhami, Zahra

AU - Oomen, Tom

AU - Barton, Kira

PY - 2019/9

Y1 - 2019/9

N2 - Spatial iterative learning control (SILC) has been used in the control of additive manufacturing systems that can be described by their spatial dynamics. Since the current framework is limited to single-layer parts, the aim of this paper is to provide an approach to multi-layer SILC using learning in the layer-to-layer dimension. Mathematical formulation of a multi-layer SILC controller is provided, and active feedback control is demonstrated to reduce the error accumulation over the iterations. Simulation results using a model of high-resolution e-jet printing verify performance improvements for the proposed framework.

AB - Spatial iterative learning control (SILC) has been used in the control of additive manufacturing systems that can be described by their spatial dynamics. Since the current framework is limited to single-layer parts, the aim of this paper is to provide an approach to multi-layer SILC using learning in the layer-to-layer dimension. Mathematical formulation of a multi-layer SILC controller is provided, and active feedback control is demonstrated to reduce the error accumulation over the iterations. Simulation results using a model of high-resolution e-jet printing verify performance improvements for the proposed framework.

KW - Control applications

KW - Feedback control

KW - Learning control

KW - Micro-additive manufacturing

KW - Spatial domain

KW - Feedback Control

KW - Micro-Additive Manufacturing

KW - Control Applications

KW - Spatial Domain

KW - Learning Control

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DO - 10.1016/j.ifacol.2019.11.657

M3 - Conference article

VL - 52

SP - 97

EP - 102

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8963

IS - 15

T2 - 8th IFAC Symposium on Mechatronic Systems (MECHATRONICS 2019), and 11th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2019) Vienna, Austria

Y2 - 4 September 2019 through 6 September 2019

ER -

Multi-layer spatial iterative learning control for micro-additive manufacturing

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Keywords

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