A Kalman Filter Approach to the Estimation and Reconstruction of Ocean Wave Fields

Zihao Chen; Jie Wu; Lian Shen; Perry Y. Li

doi:10.23919/acc55779.2023.10155910

A Kalman Filter Approach to the Estimation and Reconstruction of Ocean Wave Fields

Zihao Chen, Jie Wu, Lian Shen, Perry Y. Li

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

This paper considers the problem of real-time reconstruction of ocean wave field with a network of discrete wave height sensors. Being able to predict incoming wave characteristics helps individual or collections of wave energy converters to increase the amount of energy that they can capture. In this paper, the wave field is modeled to consist of a frequency spectrum of monotone Airy waves with unknown strengths and phases. Kalman filter based observers are then designed to estimate the wave fields. The observers' performance in reconstructing the wave field accurately is validated in simulation for 1-D and 2-D linear and nonlinear waves. Wave tank experiments have also been performed to validate its ability to reconstruct a wave field in real-time using noisy data obtained from a vision-based wave height sensor.

Original language	English (US)
Title of host publication	2023 American Control Conference, ACC 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3696-3702
Number of pages	7
ISBN (Electronic)	9798350328066
DOIs	https://doi.org/10.23919/acc55779.2023.10155910
State	Published - 2023
Externally published	Yes
Event	2023 American Control Conference, ACC 2023 - San Diego, United States Duration: May 31 2023 → Jun 2 2023

Publication series

Name	Proceedings of the American Control Conference
Volume	2023-May
ISSN (Print)	0743-1619

Conference

Conference	2023 American Control Conference, ACC 2023
Country/Territory	United States
City	San Diego
Period	5/31/23 → 6/2/23

Bibliographical note

Publisher Copyright:
© 2023 American Automatic Control Council.

Keywords

Kalman filter
Wave observer
data assimilation
high-order-spectrum method
wave tank test

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.23919/acc55779.2023.10155910

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A Kalman Filter Approach to the Estimation and Reconstruction of Ocean Wave Fields. / Chen, Zihao; Wu, Jie; Shen, Lian et al.
2023 American Control Conference, ACC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 3696-3702 (Proceedings of the American Control Conference; Vol. 2023-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chen, Z, Wu, J, Shen, L & Li, PY 2023, A Kalman Filter Approach to the Estimation and Reconstruction of Ocean Wave Fields. in 2023 American Control Conference, ACC 2023. Proceedings of the American Control Conference, vol. 2023-May, Institute of Electrical and Electronics Engineers Inc., pp. 3696-3702, 2023 American Control Conference, ACC 2023, San Diego, United States, 5/31/23. https://doi.org/10.23919/acc55779.2023.10155910

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abstract = "This paper considers the problem of real-time reconstruction of ocean wave field with a network of discrete wave height sensors. Being able to predict incoming wave characteristics helps individual or collections of wave energy converters to increase the amount of energy that they can capture. In this paper, the wave field is modeled to consist of a frequency spectrum of monotone Airy waves with unknown strengths and phases. Kalman filter based observers are then designed to estimate the wave fields. The observers' performance in reconstructing the wave field accurately is validated in simulation for 1-D and 2-D linear and nonlinear waves. Wave tank experiments have also been performed to validate its ability to reconstruct a wave field in real-time using noisy data obtained from a vision-based wave height sensor.",

keywords = "Kalman filter, Wave observer, data assimilation, high-order-spectrum method, wave tank test",

author = "Zihao Chen and Jie Wu and Lian Shen and Li, {Perry Y.}",

note = "Publisher Copyright: {\textcopyright} 2023 American Automatic Control Council.; 2023 American Control Conference, ACC 2023 ; Conference date: 31-05-2023 Through 02-06-2023",

year = "2023",

doi = "10.23919/acc55779.2023.10155910",

language = "English (US)",

series = "Proceedings of the American Control Conference",

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AU - Chen, Zihao

AU - Wu, Jie

AU - Shen, Lian

AU - Li, Perry Y.

PY - 2023

Y1 - 2023

N2 - This paper considers the problem of real-time reconstruction of ocean wave field with a network of discrete wave height sensors. Being able to predict incoming wave characteristics helps individual or collections of wave energy converters to increase the amount of energy that they can capture. In this paper, the wave field is modeled to consist of a frequency spectrum of monotone Airy waves with unknown strengths and phases. Kalman filter based observers are then designed to estimate the wave fields. The observers' performance in reconstructing the wave field accurately is validated in simulation for 1-D and 2-D linear and nonlinear waves. Wave tank experiments have also been performed to validate its ability to reconstruct a wave field in real-time using noisy data obtained from a vision-based wave height sensor.

AB - This paper considers the problem of real-time reconstruction of ocean wave field with a network of discrete wave height sensors. Being able to predict incoming wave characteristics helps individual or collections of wave energy converters to increase the amount of energy that they can capture. In this paper, the wave field is modeled to consist of a frequency spectrum of monotone Airy waves with unknown strengths and phases. Kalman filter based observers are then designed to estimate the wave fields. The observers' performance in reconstructing the wave field accurately is validated in simulation for 1-D and 2-D linear and nonlinear waves. Wave tank experiments have also been performed to validate its ability to reconstruct a wave field in real-time using noisy data obtained from a vision-based wave height sensor.

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KW - Wave observer

KW - data assimilation

KW - high-order-spectrum method

KW - wave tank test

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A Kalman Filter Approach to the Estimation and Reconstruction of Ocean Wave Fields

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

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