Accommodating trial-varying tasks in iterative learning control for LPV systems, applied to printer sheet positioning

Robin de Rozario; Remy Pelzer; Sjirk Koekcbakker; Tom Oomen

doi:10.23919/ACC.2018.8430906

Accommodating trial-varying tasks in iterative learning control for LPV systems, applied to printer sheet positioning

Robin de Rozario, Remy Pelzer, Sjirk Koekcbakker, Tom Oomen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

6 Citations (Scopus)

3 Downloads (Pure)

Abstract

Many control applications are nonlinear and have to perform a range of different tasks. Iterative Learning Control (ILC) enables high performance for a single task, but is highly sensitive to task variations. The aim of this paper is to develop an ILC framework for Linear Parameter Varying (LPV) systems, which encompasses a large class of nonlinear systems, which allows for trial-varying reference signals. This is achieved by exploiting parameter varying basis functions, such that perfect tracking is enabled for LPV systems. The proposed approach is applied to a printer sheet positioning unit, thereby validating that the tracking performance is significantly enhanced with respect to existing approaches.

Original language	English
Title of host publication	2018 Annual American Control Conference, ACC 2018
Publisher	Institute of Electrical and Electronics Engineers
Pages	5213-5218
Number of pages	6
ISBN (Print)	9781538654286
DOIs	https://doi.org/10.23919/ACC.2018.8430906
Publication status	Published - 9 Aug 2018
Event	2018 American Control Conference (ACC 2018) - Hilton Milwaukee City Center Hotel, Milwaukee, Wisconsin, United States Duration: 27 Jun 2018 → 29 Jun 2018 http://acc2018.a2c2.org/

Conference

Conference	2018 American Control Conference (ACC 2018)
Abbreviated title	ACC 2018
Country/Territory	United States
City	Milwaukee, Wisconsin
Period	27/06/18 → 29/06/18
Internet address	http://acc2018.a2c2.org/

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10.23919/ACC.2018.8430906

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title = "Accommodating trial-varying tasks in iterative learning control for LPV systems, applied to printer sheet positioning",

abstract = "Many control applications are nonlinear and have to perform a range of different tasks. Iterative Learning Control (ILC) enables high performance for a single task, but is highly sensitive to task variations. The aim of this paper is to develop an ILC framework for Linear Parameter Varying (LPV) systems, which encompasses a large class of nonlinear systems, which allows for trial-varying reference signals. This is achieved by exploiting parameter varying basis functions, such that perfect tracking is enabled for LPV systems. The proposed approach is applied to a printer sheet positioning unit, thereby validating that the tracking performance is significantly enhanced with respect to existing approaches.",

author = "{de Rozario}, Robin and Remy Pelzer and Sjirk Koekcbakker and Tom Oomen",

year = "2018",

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day = "9",

doi = "10.23919/ACC.2018.8430906",

language = "English",

isbn = "9781538654286",

pages = "5213--5218",

booktitle = "2018 Annual American Control Conference, ACC 2018",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "2018 American Control Conference (ACC 2018), ACC 2018 ; Conference date: 27-06-2018 Through 29-06-2018",

url = "http://acc2018.a2c2.org/",

}

de Rozario, R, Pelzer, R, Koekcbakker, S & Oomen, T 2018, Accommodating trial-varying tasks in iterative learning control for LPV systems, applied to printer sheet positioning. in 2018 Annual American Control Conference, ACC 2018. Institute of Electrical and Electronics Engineers, pp. 5213-5218, 2018 American Control Conference (ACC 2018), Milwaukee, Wisconsin, United States, 27/06/18. https://doi.org/10.23919/ACC.2018.8430906

Accommodating trial-varying tasks in iterative learning control for LPV systems, applied to printer sheet positioning. / de Rozario, Robin; Pelzer, Remy; Koekcbakker, Sjirk et al.
2018 Annual American Control Conference, ACC 2018. Institute of Electrical and Electronics Engineers, 2018. p. 5213-5218.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Accommodating trial-varying tasks in iterative learning control for LPV systems, applied to printer sheet positioning

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AU - Koekcbakker, Sjirk

AU - Oomen, Tom

PY - 2018/8/9

Y1 - 2018/8/9

N2 - Many control applications are nonlinear and have to perform a range of different tasks. Iterative Learning Control (ILC) enables high performance for a single task, but is highly sensitive to task variations. The aim of this paper is to develop an ILC framework for Linear Parameter Varying (LPV) systems, which encompasses a large class of nonlinear systems, which allows for trial-varying reference signals. This is achieved by exploiting parameter varying basis functions, such that perfect tracking is enabled for LPV systems. The proposed approach is applied to a printer sheet positioning unit, thereby validating that the tracking performance is significantly enhanced with respect to existing approaches.

AB - Many control applications are nonlinear and have to perform a range of different tasks. Iterative Learning Control (ILC) enables high performance for a single task, but is highly sensitive to task variations. The aim of this paper is to develop an ILC framework for Linear Parameter Varying (LPV) systems, which encompasses a large class of nonlinear systems, which allows for trial-varying reference signals. This is achieved by exploiting parameter varying basis functions, such that perfect tracking is enabled for LPV systems. The proposed approach is applied to a printer sheet positioning unit, thereby validating that the tracking performance is significantly enhanced with respect to existing approaches.

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U2 - 10.23919/ACC.2018.8430906

DO - 10.23919/ACC.2018.8430906

M3 - Conference contribution

AN - SCOPUS:85052591633

SN - 9781538654286

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EP - 5218

BT - 2018 Annual American Control Conference, ACC 2018

PB - Institute of Electrical and Electronics Engineers

T2 - 2018 American Control Conference (ACC 2018)

Y2 - 27 June 2018 through 29 June 2018

ER -

Accommodating trial-varying tasks in iterative learning control for LPV systems, applied to printer sheet positioning

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