Nonlinear Repetitive Control for Mitigating Noise Amplification

L.I.M. Aarnoudse; Alexei Pavlov; J.J. Kon; Tom A.E. Oomen

doi:10.1109/CDC49753.2023.10383495

Nonlinear Repetitive Control for Mitigating Noise Amplification

L.I.M. Aarnoudse
, Alexei Pavlov
, J.J. Kon
, Tom A.E. Oomen

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

2 Citations (Scopus)

347 Downloads (Pure)

Abstract

Repetitive control can lead to high performance by attenuating periodic disturbances completely, yet it may amplify non-periodic disturbances. The aim of this paper is to achieve both fast learning and low errors in repetitive control. To this end, a nonlinear learning filter is introduced that distinguishes between periodic and non-periodic errors based on their typical amplitude characteristics to adapt the extent to which they are included in the repetitive controller. Convergence conditions for the nonlinear repetitive control system are derived by casting the resulting closed-loop as a discrete-time convergent system. Simulation results of the proposed approach demonstrate fast learning and small errors.

Original language	English
Title of host publication	2023 62nd IEEE Conference on Decision and Control, CDC 2023
Publisher	Institute of Electrical and Electronics Engineers
Pages	2891-2896
Number of pages	6
ISBN (Electronic)	979-8-3503-0124-3
DOIs	https://doi.org/10.1109/CDC49753.2023.10383495
Publication status	Published - 19 Jan 2024
Event	62nd IEEE Conference on Decision and Control, CDC 2023 - Singapore, Singapore Duration: 13 Dec 2023 → 15 Dec 2023 Conference number: 62

Conference

Conference	62nd IEEE Conference on Decision and Control, CDC 2023
Abbreviated title	CDC 2023
Country/Territory	Singapore
City	Singapore
Period	13/12/23 → 15/12/23

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10.1109/CDC49753.2023.10383495

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pdfFinal published version, 857 KBLicence: TAVERNE

Cite this

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title = "Nonlinear Repetitive Control for Mitigating Noise Amplification",

abstract = "Repetitive control can lead to high performance by attenuating periodic disturbances completely, yet it may amplify non-periodic disturbances. The aim of this paper is to achieve both fast learning and low errors in repetitive control. To this end, a nonlinear learning filter is introduced that distinguishes between periodic and non-periodic errors based on their typical amplitude characteristics to adapt the extent to which they are included in the repetitive controller. Convergence conditions for the nonlinear repetitive control system are derived by casting the resulting closed-loop as a discrete-time convergent system. Simulation results of the proposed approach demonstrate fast learning and small errors.",

author = "L.I.M. Aarnoudse and Alexei Pavlov and J.J. Kon and Oomen, \{Tom A.E.\}",

year = "2024",

month = jan,

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doi = "10.1109/CDC49753.2023.10383495",

language = "English",

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booktitle = "2023 62nd IEEE Conference on Decision and Control, CDC 2023",

publisher = "Institute of Electrical and Electronics Engineers",

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note = "62nd IEEE Conference on Decision and Control, CDC 2023, CDC 2023 ; Conference date: 13-12-2023 Through 15-12-2023",

}

Aarnoudse, LIM, Pavlov, A, Kon, JJ & Oomen, TAE 2024, Nonlinear Repetitive Control for Mitigating Noise Amplification. in 2023 62nd IEEE Conference on Decision and Control, CDC 2023., 10383495, Institute of Electrical and Electronics Engineers, pp. 2891-2896, 62nd IEEE Conference on Decision and Control, CDC 2023, Singapore, Singapore, 13/12/23. https://doi.org/10.1109/CDC49753.2023.10383495

Nonlinear Repetitive Control for Mitigating Noise Amplification. / Aarnoudse, L.I.M.; Pavlov, Alexei; Kon, J.J. et al.
2023 62nd IEEE Conference on Decision and Control, CDC 2023. Institute of Electrical and Electronics Engineers, 2024. p. 2891-2896 10383495.

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

TY - GEN

T1 - Nonlinear Repetitive Control for Mitigating Noise Amplification

AU - Aarnoudse, L.I.M.

AU - Pavlov, Alexei

AU - Kon, J.J.

AU - Oomen, Tom A.E.

N1 - Conference code: 62

PY - 2024/1/19

Y1 - 2024/1/19

N2 - Repetitive control can lead to high performance by attenuating periodic disturbances completely, yet it may amplify non-periodic disturbances. The aim of this paper is to achieve both fast learning and low errors in repetitive control. To this end, a nonlinear learning filter is introduced that distinguishes between periodic and non-periodic errors based on their typical amplitude characteristics to adapt the extent to which they are included in the repetitive controller. Convergence conditions for the nonlinear repetitive control system are derived by casting the resulting closed-loop as a discrete-time convergent system. Simulation results of the proposed approach demonstrate fast learning and small errors.

AB - Repetitive control can lead to high performance by attenuating periodic disturbances completely, yet it may amplify non-periodic disturbances. The aim of this paper is to achieve both fast learning and low errors in repetitive control. To this end, a nonlinear learning filter is introduced that distinguishes between periodic and non-periodic errors based on their typical amplitude characteristics to adapt the extent to which they are included in the repetitive controller. Convergence conditions for the nonlinear repetitive control system are derived by casting the resulting closed-loop as a discrete-time convergent system. Simulation results of the proposed approach demonstrate fast learning and small errors.

UR - https://www.scopus.com/pages/publications/85184826805

U2 - 10.1109/CDC49753.2023.10383495

DO - 10.1109/CDC49753.2023.10383495

M3 - Conference contribution

SP - 2891

EP - 2896

BT - 2023 62nd IEEE Conference on Decision and Control, CDC 2023

PB - Institute of Electrical and Electronics Engineers

T2 - 62nd IEEE Conference on Decision and Control, CDC 2023

Y2 - 13 December 2023 through 15 December 2023

ER -

Nonlinear Repetitive Control for Mitigating Noise Amplification

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