Learning Control Applied to a Digital-to-analogue Converter

Noa van Rijt; Ahmad Faza; Tom Oomen; Arnfinn A. Eielsen

doi:10.1109/CCTA54093.2023.10252330

Learning Control Applied to a Digital-to-analogue Converter

Noa van Rijt
, Ahmad Faza
, Tom Oomen
, Arnfinn A. Eielsen

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

1 Citation (Scopus)

7 Downloads (Pure)

Abstract

Digital-to-analogue converters (DACs) exhibit several non-ideal effects that deteriorate performance. Methods in feedback control can reduce such effects. Due to implementation limitations, the feedback signal in existing schemes is produced by open-loop observers, known as ΔΣ-modulation, that mitigate the observed adverse effects only partially. Measurement feedback can compensate for non-ideal behaviour and disturbances that are difficult to model. Learning control (LC) is introduced to overcome practical problems of measurement feedback in DACs, therewith omitting the need for accurate open-loop observers. Experimental results demonstrate a 95% improvement in RMS error when using LC with measurement feedback, compared to ΔΣ-modulation using observer feedback.

Original language	English
Title of host publication	2023 IEEE Conference on Control Technology and Applications, CCTA 2023
Publisher	Institute of Electrical and Electronics Engineers
Pages	91-96
Number of pages	6
ISBN (Electronic)	979-8-3503-3544-6
DOIs	https://doi.org/10.1109/CCTA54093.2023.10252330
Publication status	Published - 22 Sept 2023
Event	2023 IEEE Conference on Control Technology and Applications, CCTA 2023 - Bridgetown, Barbados Duration: 16 Aug 2023 → 18 Aug 2023

Conference

Conference	2023 IEEE Conference on Control Technology and Applications, CCTA 2023
Country/Territory	Barbados
City	Bridgetown
Period	16/08/23 → 18/08/23

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10.1109/CCTA54093.2023.10252330

pdfFinal published version, 1.96 MBLicence: TAVERNE

Cite this

@inproceedings{f796d4addb3143afbfd02be80d908ff9,

title = "Learning Control Applied to a Digital-to-analogue Converter",

abstract = "Digital-to-analogue converters (DACs) exhibit several non-ideal effects that deteriorate performance. Methods in feedback control can reduce such effects. Due to implementation limitations, the feedback signal in existing schemes is produced by open-loop observers, known as ΔΣ-modulation, that mitigate the observed adverse effects only partially. Measurement feedback can compensate for non-ideal behaviour and disturbances that are difficult to model. Learning control (LC) is introduced to overcome practical problems of measurement feedback in DACs, therewith omitting the need for accurate open-loop observers. Experimental results demonstrate a 95\% improvement in RMS error when using LC with measurement feedback, compared to ΔΣ-modulation using observer feedback.",

author = "\{van Rijt\}, Noa and Ahmad Faza and Tom Oomen and Eielsen, \{Arnfinn A.\}",

year = "2023",

month = sep,

day = "22",

doi = "10.1109/CCTA54093.2023.10252330",

language = "English",

pages = "91--96",

booktitle = "2023 IEEE Conference on Control Technology and Applications, CCTA 2023",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "2023 IEEE Conference on Control Technology and Applications, CCTA 2023 ; Conference date: 16-08-2023 Through 18-08-2023",

}

van Rijt, N, Faza, A, Oomen, T & Eielsen, AA 2023, Learning Control Applied to a Digital-to-analogue Converter. in 2023 IEEE Conference on Control Technology and Applications, CCTA 2023., 10252330, Institute of Electrical and Electronics Engineers, pp. 91-96, 2023 IEEE Conference on Control Technology and Applications, CCTA 2023, Bridgetown, Barbados, 16/08/23. https://doi.org/10.1109/CCTA54093.2023.10252330

Learning Control Applied to a Digital-to-analogue Converter. / van Rijt, Noa; Faza, Ahmad; Oomen, Tom et al.
2023 IEEE Conference on Control Technology and Applications, CCTA 2023. Institute of Electrical and Electronics Engineers, 2023. p. 91-96 10252330.

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

TY - GEN

T1 - Learning Control Applied to a Digital-to-analogue Converter

AU - van Rijt, Noa

AU - Faza, Ahmad

AU - Oomen, Tom

AU - Eielsen, Arnfinn A.

PY - 2023/9/22

Y1 - 2023/9/22

N2 - Digital-to-analogue converters (DACs) exhibit several non-ideal effects that deteriorate performance. Methods in feedback control can reduce such effects. Due to implementation limitations, the feedback signal in existing schemes is produced by open-loop observers, known as ΔΣ-modulation, that mitigate the observed adverse effects only partially. Measurement feedback can compensate for non-ideal behaviour and disturbances that are difficult to model. Learning control (LC) is introduced to overcome practical problems of measurement feedback in DACs, therewith omitting the need for accurate open-loop observers. Experimental results demonstrate a 95% improvement in RMS error when using LC with measurement feedback, compared to ΔΣ-modulation using observer feedback.

AB - Digital-to-analogue converters (DACs) exhibit several non-ideal effects that deteriorate performance. Methods in feedback control can reduce such effects. Due to implementation limitations, the feedback signal in existing schemes is produced by open-loop observers, known as ΔΣ-modulation, that mitigate the observed adverse effects only partially. Measurement feedback can compensate for non-ideal behaviour and disturbances that are difficult to model. Learning control (LC) is introduced to overcome practical problems of measurement feedback in DACs, therewith omitting the need for accurate open-loop observers. Experimental results demonstrate a 95% improvement in RMS error when using LC with measurement feedback, compared to ΔΣ-modulation using observer feedback.

UR - https://www.scopus.com/pages/publications/85173834867

U2 - 10.1109/CCTA54093.2023.10252330

DO - 10.1109/CCTA54093.2023.10252330

M3 - Conference contribution

AN - SCOPUS:85173834867

SP - 91

EP - 96

BT - 2023 IEEE Conference on Control Technology and Applications, CCTA 2023

PB - Institute of Electrical and Electronics Engineers

T2 - 2023 IEEE Conference on Control Technology and Applications, CCTA 2023

Y2 - 16 August 2023 through 18 August 2023

ER -

Learning Control Applied to a Digital-to-analogue Converter

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