Hybrid-MEM-Element Feedforward: WIth Application to Hysteretic Piezoelectric Actuators

Nard Strijbosch; Tom Oomen

doi:10.1109/CDC42340.2020.9304407

Hybrid-MEM-Element Feedforward: WIth Application to Hysteretic Piezoelectric Actuators

Nard Strijbosch
, Tom Oomen

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

4 Citaten (Scopus)

15 Downloads (Pure)

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Hysteresis phenomena can significantly deteriorate the performance when performing servo tasks with piezo-electric actuators. The aim of this paper is to model this non-linear hysteresis effect using a memory element, in particular a MEM-element, and exploit this model to develop a feedforward controller. A one-to-one mapping is established, leading to both a systematic data-driven learning approach of a hybrid-MEM-element capturing the hysteresis phenomena and a unique inverse allowing for an intuitive design of the feedforward controller. The developed approach is experimentally validated on a piezoelectric actuator, revealing a significant performance improvement.

Originele taal-2	Engels
Titel	59th IEEE Conference on Decision and Control (CDC 2020)
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	934-939
Aantal pagina's	6
ISBN van elektronische versie	9781728174471
DOI's	https://doi.org/10.1109/CDC42340.2020.9304407
Status	Gepubliceerd - 11 jan. 2021
Evenement	2020 59th IEEE Conference on Decision and Control (CDC) - Virtual/Online, Virtual, Jeju Island, Zuid-Korea Duur: 14 dec. 2020 → 18 dec. 2020 Congresnummer: 59 https://cdc2020.ieeecss.org/

Congres

Congres	2020 59th IEEE Conference on Decision and Control (CDC)
Verkorte titel	CDC
Land/Regio	Zuid-Korea
Stad	Virtual, Jeju Island
Periode	14/12/20 → 18/12/20
Internet adres	https://cdc2020.ieeecss.org/

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10.1109/CDC42340.2020.9304407

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title = "Hybrid-MEM-Element Feedforward: WIth Application to Hysteretic Piezoelectric Actuators",

abstract = "Hysteresis phenomena can significantly deteriorate the performance when performing servo tasks with piezo-electric actuators. The aim of this paper is to model this non-linear hysteresis effect using a memory element, in particular a MEM-element, and exploit this model to develop a feedforward controller. A one-to-one mapping is established, leading to both a systematic data-driven learning approach of a hybrid-MEM-element capturing the hysteresis phenomena and a unique inverse allowing for an intuitive design of the feedforward controller. The developed approach is experimentally validated on a piezoelectric actuator, revealing a significant performance improvement.",

author = "Nard Strijbosch and Tom Oomen",

year = "2021",

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doi = "10.1109/CDC42340.2020.9304407",

language = "English",

pages = "934--939",

booktitle = "59th IEEE Conference on Decision and Control (CDC 2020)",

publisher = "Institute of Electrical and Electronics Engineers",

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}

Strijbosch, N & Oomen, T 2021, Hybrid-MEM-Element Feedforward: WIth Application to Hysteretic Piezoelectric Actuators. in 59th IEEE Conference on Decision and Control (CDC 2020)., 9304407, Institute of Electrical and Electronics Engineers, blz. 934-939, 2020 59th IEEE Conference on Decision and Control (CDC), Virtual, Jeju Island, Zuid-Korea, 14/12/20. https://doi.org/10.1109/CDC42340.2020.9304407

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AU - Oomen, Tom

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Y1 - 2021/1/11

N2 - Hysteresis phenomena can significantly deteriorate the performance when performing servo tasks with piezo-electric actuators. The aim of this paper is to model this non-linear hysteresis effect using a memory element, in particular a MEM-element, and exploit this model to develop a feedforward controller. A one-to-one mapping is established, leading to both a systematic data-driven learning approach of a hybrid-MEM-element capturing the hysteresis phenomena and a unique inverse allowing for an intuitive design of the feedforward controller. The developed approach is experimentally validated on a piezoelectric actuator, revealing a significant performance improvement.

AB - Hysteresis phenomena can significantly deteriorate the performance when performing servo tasks with piezo-electric actuators. The aim of this paper is to model this non-linear hysteresis effect using a memory element, in particular a MEM-element, and exploit this model to develop a feedforward controller. A one-to-one mapping is established, leading to both a systematic data-driven learning approach of a hybrid-MEM-element capturing the hysteresis phenomena and a unique inverse allowing for an intuitive design of the feedforward controller. The developed approach is experimentally validated on a piezoelectric actuator, revealing a significant performance improvement.

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DO - 10.1109/CDC42340.2020.9304407

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BT - 59th IEEE Conference on Decision and Control (CDC 2020)

PB - Institute of Electrical and Electronics Engineers

Y2 - 14 December 2020 through 18 December 2020

ER -

Hybrid-MEM-Element Feedforward: WIth Application to Hysteretic Piezoelectric Actuators

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