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Numerical continuation in nonlinear experiments using local Gaussian process regression

L. Renson, J. Sieber, D. A. W. Barton, Alexander Shaw Orcid Logo, S. A. Neild

Nonlinear Dynamics, Volume: 98, Issue: 4, Pages: 2811 - 2826

Swansea University Author: Alexander Shaw Orcid Logo

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DOI (Published version): 10.1007/s11071-019-05118-y

Abstract

Control-based continuation (CBC) is a general and systematic method to probe the dynamics of nonlinear experiments. In this paper, CBC is combined with a novel continuation algorithm that is robust to experimental noise and enables the tracking of geometric features of the response surface such as f...

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Published in: Nonlinear Dynamics
ISSN: 0924-090X 1573-269X
Published: Springer Science and Business Media LLC 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa51462
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first_indexed 2019-08-19T15:29:38Z
last_indexed 2020-11-20T04:06:09Z
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spelling 2020-11-19T16:57:21.3812641 v2 51462 2019-08-19 Numerical continuation in nonlinear experiments using local Gaussian process regression 10cb5f545bc146fba9a542a1d85f2dea 0000-0002-7521-827X Alexander Shaw Alexander Shaw true false 2019-08-19 AERO Control-based continuation (CBC) is a general and systematic method to probe the dynamics of nonlinear experiments. In this paper, CBC is combined with a novel continuation algorithm that is robust to experimental noise and enables the tracking of geometric features of the response surface such as folds. The method uses Gaussian process regression to create a local model of the response surface on which standard numerical continuation algorithms can be applied. The local model evolves as continuation explores the experimental parameter space, exploiting previously captured data to actively select the next data points to collect such that they maximise the potential information gain about the feature of interest. The method is demonstrated experimentally on a nonlinear structure featuring harmonically coupled modes. Fold points present in the response surface of the system are followed and reveal the presence of an isola, i.e. a branch of periodic responses detached from the main resonance peak. Journal Article Nonlinear Dynamics 98 4 2811 2826 Springer Science and Business Media LLC 0924-090X 1573-269X Nonlinear experiment, Control-based continuation, Regression-based continuation, Gaussian process regression, Active data selection 1 12 2019 2019-12-01 10.1007/s11071-019-05118-y COLLEGE NANME Aerospace Engineering COLLEGE CODE AERO Swansea University 2020-11-19T16:57:21.3812641 2019-08-19T09:31:41.1720509 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering L. Renson 1 J. Sieber 2 D. A. W. Barton 3 Alexander Shaw 0000-0002-7521-827X 4 S. A. Neild 5 0051462-22082019104243.pdf renson2019.pdf 2019-08-22T10:42:43.1870000 Output 1333578 application/pdf Accepted Manuscript true 2020-08-08T00:00:00.0000000 true eng
title Numerical continuation in nonlinear experiments using local Gaussian process regression
spellingShingle Numerical continuation in nonlinear experiments using local Gaussian process regression
Alexander Shaw
title_short Numerical continuation in nonlinear experiments using local Gaussian process regression
title_full Numerical continuation in nonlinear experiments using local Gaussian process regression
title_fullStr Numerical continuation in nonlinear experiments using local Gaussian process regression
title_full_unstemmed Numerical continuation in nonlinear experiments using local Gaussian process regression
title_sort Numerical continuation in nonlinear experiments using local Gaussian process regression
author_id_str_mv 10cb5f545bc146fba9a542a1d85f2dea
author_id_fullname_str_mv 10cb5f545bc146fba9a542a1d85f2dea_***_Alexander Shaw
author Alexander Shaw
author2 L. Renson
J. Sieber
D. A. W. Barton
Alexander Shaw
S. A. Neild
format Journal article
container_title Nonlinear Dynamics
container_volume 98
container_issue 4
container_start_page 2811
publishDate 2019
institution Swansea University
issn 0924-090X
1573-269X
doi_str_mv 10.1007/s11071-019-05118-y
publisher Springer Science and Business Media LLC
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering
document_store_str 1
active_str 0
description Control-based continuation (CBC) is a general and systematic method to probe the dynamics of nonlinear experiments. In this paper, CBC is combined with a novel continuation algorithm that is robust to experimental noise and enables the tracking of geometric features of the response surface such as folds. The method uses Gaussian process regression to create a local model of the response surface on which standard numerical continuation algorithms can be applied. The local model evolves as continuation explores the experimental parameter space, exploiting previously captured data to actively select the next data points to collect such that they maximise the potential information gain about the feature of interest. The method is demonstrated experimentally on a nonlinear structure featuring harmonically coupled modes. Fold points present in the response surface of the system are followed and reveal the presence of an isola, i.e. a branch of periodic responses detached from the main resonance peak.
published_date 2019-12-01T04:03:21Z
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score 10.998093

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