Learning in the synthesis of data-driven variable-gain controllers

M.F. Heertjes; B.G.B. Hunnekens; N. Wouw, van de; H. Nijmeijer

doi:10.1109/ACC.2013.6580889

Learning in the synthesis of data-driven variable-gain controllers

Dynamics and Control

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

7 Citations (Scopus)

Abstract

To deal with performance trade-offs in the control of motion systems, a method is developed for designing variable-gain feedback controllers. The idea is to select a piecewise affine controller structure and, subsequently, to find the nonlinear controller parameter values of this structure by data-driven performance optimization. Herein an ℌ 2 performance objective is minimized. As a result, variable-gain controllers are synthesized using techniques from the field of learning and optimization. The method is applied to a wafer stage simulation model.

Original language	English
Title of host publication	2013 ACC conference
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	6685-6690
Number of pages	6
ISBN (Electronic)	978-1-4799-0178-4
ISBN (Print)	978-1-4799-0177-7
DOIs	https://doi.org/10.1109/ACC.2013.6580889
Publication status	Published - 2013
Event	2013 American Control Conference (ACC 2013), June 17-19, 2013, Washington, DC, USA - Renaissance Washington, DC Downtown Hotel, Washington, DC, United States Duration: 17 Jun 2013 → 19 Jun 2013 http://acc2013.a2c2.org/

Conference

Conference	2013 American Control Conference (ACC 2013), June 17-19, 2013, Washington, DC, USA
Abbreviated title	ACC 2013
Country/Territory	United States
City	Washington, DC
Period	17/06/13 → 19/06/13
Internet address	http://acc2013.a2c2.org/

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10.1109/ACC.2013.6580889

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title = "Learning in the synthesis of data-driven variable-gain controllers",

abstract = "To deal with performance trade-offs in the control of motion systems, a method is developed for designing variable-gain feedback controllers. The idea is to select a piecewise affine controller structure and, subsequently, to find the nonlinear controller parameter values of this structure by data-driven performance optimization. Herein an ℌ 2 performance objective is minimized. As a result, variable-gain controllers are synthesized using techniques from the field of learning and optimization. The method is applied to a wafer stage simulation model.",

author = "M.F. Heertjes and B.G.B. Hunnekens and \{Wouw, van de\}, N. and H. Nijmeijer",

year = "2013",

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language = "English",

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publisher = "Institute of Electrical and Electronics Engineers",

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note = "2013 American Control Conference (ACC 2013), June 17-19, 2013, Washington, DC, USA, ACC 2013 ; Conference date: 17-06-2013 Through 19-06-2013",

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Heertjes, MF, Hunnekens, BGB, Wouw, van de, N & Nijmeijer, H 2013, Learning in the synthesis of data-driven variable-gain controllers. in 2013 ACC conference. Institute of Electrical and Electronics Engineers, Piscataway, pp. 6685-6690, 2013 American Control Conference (ACC 2013), June 17-19, 2013, Washington, DC, USA, Washington, DC, United States, 17/06/13. https://doi.org/10.1109/ACC.2013.6580889

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AU - Hunnekens, B.G.B.

AU - Wouw, van de, N.

AU - Nijmeijer, H.

PY - 2013

Y1 - 2013

N2 - To deal with performance trade-offs in the control of motion systems, a method is developed for designing variable-gain feedback controllers. The idea is to select a piecewise affine controller structure and, subsequently, to find the nonlinear controller parameter values of this structure by data-driven performance optimization. Herein an ℌ 2 performance objective is minimized. As a result, variable-gain controllers are synthesized using techniques from the field of learning and optimization. The method is applied to a wafer stage simulation model.

AB - To deal with performance trade-offs in the control of motion systems, a method is developed for designing variable-gain feedback controllers. The idea is to select a piecewise affine controller structure and, subsequently, to find the nonlinear controller parameter values of this structure by data-driven performance optimization. Herein an ℌ 2 performance objective is minimized. As a result, variable-gain controllers are synthesized using techniques from the field of learning and optimization. The method is applied to a wafer stage simulation model.

U2 - 10.1109/ACC.2013.6580889

DO - 10.1109/ACC.2013.6580889

M3 - Conference contribution

SN - 978-1-4799-0177-7

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EP - 6690

BT - 2013 ACC conference

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

T2 - 2013 American Control Conference (ACC 2013), June 17-19, 2013, Washington, DC, USA

Y2 - 17 June 2013 through 19 June 2013

ER -

Learning in the synthesis of data-driven variable-gain controllers

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