Enabling high precision for position-dependent motion systems using iterative learning control

R. de Rozario; T.A.E. Oomen

Enabling high precision for position-dependent motion systems using iterative learning control

Vertaalde titel van de bijdrage: Hoge precisie mogelijk maken voor positieafhankelijke motion systemen door middel van iteratief lerend regelen

R. de Rozario
, T.A.E. Oomen

Control Systems Technology

Onderzoeksoutput: Bijdrage aan congres › Paper › Academic

Samenvatting

Increasing accuracy and speed requirements on next-generation motion systems lead to situation where position-dependent effects hamper the achievable performance. Traditional Iterative Learning Control (ILC) methods are insufficiently developed to achieve high performance for position-dependent systems. This paper highlights key results from recent developments that aim to fill this gap by generalizing ILC to Linear Parameter-Varying (LPV) systems.

Vertaalde titel van de bijdrage	Hoge precisie mogelijk maken voor positieafhankelijke motion systemen door middel van iteratief lerend regelen
Originele taal-2	Engels
Status	Gepubliceerd - 8 mrt. 2018
Evenement	IEEJ International Workshop on Sensing, Actuation, Motion Control, and Optimization - Tokyo Denki University, Tokyo, Japan Duur: 6 mrt. 2018 → 8 mrt. 2018 Congresnummer: 4 http://www2.iee.or.jp/~diic/samcon/

Congres

Congres	IEEJ International Workshop on Sensing, Actuation, Motion Control, and Optimization
Verkorte titel	SAMCON 2018
Land/Regio	Japan
Stad	Tokyo
Periode	6/03/18 → 8/03/18
Internet adres	http://www2.iee.or.jp/~diic/samcon/

Andere bestanden en links

Citeer dit

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title = "Enabling high precision for position-dependent motion systems using iterative learning control",

abstract = "Increasing accuracy and speed requirements on next-generation motion systems lead to situation where position-dependent effects hamper the achievable performance. Traditional Iterative Learning Control (ILC) methods are insufficiently developed to achieve high performance for position-dependent systems. This paper highlights key results from recent developments that aim to fill this gap by generalizing ILC to Linear Parameter-Varying (LPV) systems.",

keywords = "iterative learning control (ILC), Motion control, linear parameter varying systems",

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year = "2018",

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note = "4th IEEJ International Workshop on Sensing, Actuation, Motion Control, and Optimization (SAMCON 2018), SAMCON 2018 ; Conference date: 06-03-2018 Through 08-03-2018",

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AU - de Rozario, R.

AU - Oomen, T.A.E.

N1 - Conference code: 4

PY - 2018/3/8

Y1 - 2018/3/8

N2 - Increasing accuracy and speed requirements on next-generation motion systems lead to situation where position-dependent effects hamper the achievable performance. Traditional Iterative Learning Control (ILC) methods are insufficiently developed to achieve high performance for position-dependent systems. This paper highlights key results from recent developments that aim to fill this gap by generalizing ILC to Linear Parameter-Varying (LPV) systems.

AB - Increasing accuracy and speed requirements on next-generation motion systems lead to situation where position-dependent effects hamper the achievable performance. Traditional Iterative Learning Control (ILC) methods are insufficiently developed to achieve high performance for position-dependent systems. This paper highlights key results from recent developments that aim to fill this gap by generalizing ILC to Linear Parameter-Varying (LPV) systems.

KW - iterative learning control (ILC)

KW - Motion control

KW - linear parameter varying systems

M3 - Paper

T2 - 4th IEEJ International Workshop on Sensing, Actuation, Motion Control, and Optimization (SAMCON 2018)

Y2 - 6 March 2018 through 8 March 2018

ER -