Rational iterative feedforward tuning: Approaches, stable inversion, and experimental comparison

L.L.G. Blanken; F.A.J. Boeren; D.J.H. Bruijnen; T.A.E. Oomen

doi:10.1109/ACC.2016.7525313

Rational iterative feedforward tuning: Approaches, stable inversion, and experimental comparison

L.L.G. Blanken
, F.A.J. Boeren
, D.J.H. Bruijnen
, T.A.E. Oomen

Control Systems Technology

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

14 Citations (Scopus)

2 Downloads (Pure)

Abstract

Feedforward control plays a key role in achieving high performance for industrial motion systems that perform non-repeating motion tasks. Recently, learning techniques have been proposed to further improve both performance and robustness to non-repeating tasks by using a rational feedforward basis. The aim of this paper is to propose a unifying framework which connects these approaches. Experimental results on an industrial motion system validate the approaches and illustrate benefits of rational feedforward tuning in motion systems, including pre- and post-actuation through stable inversion.

Original language	English
Title of host publication	2016 American Control Conference (ACC 2016), July 6-8, 2016, Boston, MA, USA
Publisher	American Automatic Control Council (AACC)
Pages	2629-2634
ISBN (Electronic)	978-1-4673-8682-1
DOIs	https://doi.org/10.1109/ACC.2016.7525313
Publication status	Published - 2016
Event	2016 American Control Conference (ACC 2016), July 6-8, 2016, Boston, MA, USA - Boston Marriott Copley Place, Boston, MA, United States Duration: 6 Jul 2016 → 8 Jul 2016 http://acc2016.a2c2.org/

Conference

Conference	2016 American Control Conference (ACC 2016), July 6-8, 2016, Boston, MA, USA
Abbreviated title	ACC 2016
Country/Territory	United States
City	Boston, MA
Period	6/07/16 → 8/07/16
Internet address	http://acc2016.a2c2.org/

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10.1109/ACC.2016.7525313

Cite this

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title = "Rational iterative feedforward tuning: Approaches, stable inversion, and experimental comparison",

abstract = "Feedforward control plays a key role in achieving high performance for industrial motion systems that perform non-repeating motion tasks. Recently, learning techniques have been proposed to further improve both performance and robustness to non-repeating tasks by using a rational feedforward basis. The aim of this paper is to propose a unifying framework which connects these approaches. Experimental results on an industrial motion system validate the approaches and illustrate benefits of rational feedforward tuning in motion systems, including pre- and post-actuation through stable inversion.",

author = "L.L.G. Blanken and F.A.J. Boeren and D.J.H. Bruijnen and T.A.E. Oomen",

year = "2016",

doi = "10.1109/ACC.2016.7525313",

language = "English",

pages = "2629--2634",

booktitle = "2016 American Control Conference (ACC 2016), July 6-8, 2016, Boston, MA, USA",

publisher = "American Automatic Control Council (AACC)",

note = "2016 American Control Conference (ACC 2016), July 6-8, 2016, Boston, MA, USA, ACC 2016 ; Conference date: 06-07-2016 Through 08-07-2016",

url = "http://acc2016.a2c2.org/",

}

Blanken, LLG, Boeren, FAJ, Bruijnen, DJH & Oomen, TAE 2016, Rational iterative feedforward tuning: Approaches, stable inversion, and experimental comparison. in 2016 American Control Conference (ACC 2016), July 6-8, 2016, Boston, MA, USA. American Automatic Control Council (AACC), pp. 2629-2634, 2016 American Control Conference (ACC 2016), July 6-8, 2016, Boston, MA, USA, Boston, MA, United States, 6/07/16. https://doi.org/10.1109/ACC.2016.7525313

Rational iterative feedforward tuning: Approaches, stable inversion, and experimental comparison. / Blanken, L.L.G.; Boeren, F.A.J.; Bruijnen, D.J.H. et al.
2016 American Control Conference (ACC 2016), July 6-8, 2016, Boston, MA, USA. American Automatic Control Council (AACC), 2016. p. 2629-2634.

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

TY - GEN

T1 - Rational iterative feedforward tuning: Approaches, stable inversion, and experimental comparison

AU - Blanken, L.L.G.

AU - Boeren, F.A.J.

AU - Bruijnen, D.J.H.

AU - Oomen, T.A.E.

PY - 2016

Y1 - 2016

N2 - Feedforward control plays a key role in achieving high performance for industrial motion systems that perform non-repeating motion tasks. Recently, learning techniques have been proposed to further improve both performance and robustness to non-repeating tasks by using a rational feedforward basis. The aim of this paper is to propose a unifying framework which connects these approaches. Experimental results on an industrial motion system validate the approaches and illustrate benefits of rational feedforward tuning in motion systems, including pre- and post-actuation through stable inversion.

AB - Feedforward control plays a key role in achieving high performance for industrial motion systems that perform non-repeating motion tasks. Recently, learning techniques have been proposed to further improve both performance and robustness to non-repeating tasks by using a rational feedforward basis. The aim of this paper is to propose a unifying framework which connects these approaches. Experimental results on an industrial motion system validate the approaches and illustrate benefits of rational feedforward tuning in motion systems, including pre- and post-actuation through stable inversion.

U2 - 10.1109/ACC.2016.7525313

DO - 10.1109/ACC.2016.7525313

M3 - Conference contribution

SP - 2629

EP - 2634

BT - 2016 American Control Conference (ACC 2016), July 6-8, 2016, Boston, MA, USA

PB - American Automatic Control Council (AACC)

T2 - 2016 American Control Conference (ACC 2016), July 6-8, 2016, Boston, MA, USA

Y2 - 6 July 2016 through 8 July 2016

ER -

Rational iterative feedforward tuning: Approaches, stable inversion, and experimental comparison

Abstract

Conference

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