Robust excitation force estimation and prediction for wave energy converter M4 based on adaptive sliding-mode observer
Robust excitation force estimation and prediction for wave energy converter M4 based on adaptive sliding-mode observer
The wave excitation force estimation and prediction play an important role in improving the performance of causal and noncausal controllers for wave energy converters (WECs). This article proposes a robust adaptive sliding-mode observer (ASMO) to estimate the wave excitation force subject to unknown disturbances and parametric uncertainties for a multimotion multifloat WEC, called M4. Both the convergence time and the estimation error can be explicitly bounded within expected limits by tuning the ASMO parameters, which are essentially beneficial for causal controllers to maintain the control performance. A fixed-time convergent sliding variable is designed to drive the estimation error into a small region within a fixed time. Due to the adaptive law, the overall system is proven to be finite-time stable, which allows explicit formulations of the convergence time and the estimation error. Moreover, based on the wave force estimation by the ASMO, an improved auto-regressive (AR) model whose coefficients are updated by online training is developed to predict the wave excitation force. The prediction errors can also be explicitly estimated to achieve guaranteed control performance for the noncausal controller requiring future excitation force. From the comparison based on a realistic sea wave gathered from Cornwall, U.K., it can be found that compared with the conventional Kalman filter, the ASMO achieves a smaller steady-state estimation error and has satisfactory robustness performance against 30% model mismatch.
M4, robustness, sliding-mode observer (SMO), wave energy converters, wave excitation force
1163-1171
Zhang, Yao
a4f30318-ab42-4b38-a60d-f7199ff3a02a
Zeng, Tianyi
0c259925-4a87-4aaf-b373-215f65c56298
Li, Guang
76def2e4-4cf4-43b3-8b4c-78c7111d8ef3
1 February 2020
Zhang, Yao
a4f30318-ab42-4b38-a60d-f7199ff3a02a
Zeng, Tianyi
0c259925-4a87-4aaf-b373-215f65c56298
Li, Guang
76def2e4-4cf4-43b3-8b4c-78c7111d8ef3
Zhang, Yao, Zeng, Tianyi and Li, Guang
(2020)
Robust excitation force estimation and prediction for wave energy converter M4 based on adaptive sliding-mode observer.
IEEE Transactions on Industrial Informatics, 16 (2), .
(doi:10.1109/TII.2019.2941886).
Abstract
The wave excitation force estimation and prediction play an important role in improving the performance of causal and noncausal controllers for wave energy converters (WECs). This article proposes a robust adaptive sliding-mode observer (ASMO) to estimate the wave excitation force subject to unknown disturbances and parametric uncertainties for a multimotion multifloat WEC, called M4. Both the convergence time and the estimation error can be explicitly bounded within expected limits by tuning the ASMO parameters, which are essentially beneficial for causal controllers to maintain the control performance. A fixed-time convergent sliding variable is designed to drive the estimation error into a small region within a fixed time. Due to the adaptive law, the overall system is proven to be finite-time stable, which allows explicit formulations of the convergence time and the estimation error. Moreover, based on the wave force estimation by the ASMO, an improved auto-regressive (AR) model whose coefficients are updated by online training is developed to predict the wave excitation force. The prediction errors can also be explicitly estimated to achieve guaranteed control performance for the noncausal controller requiring future excitation force. From the comparison based on a realistic sea wave gathered from Cornwall, U.K., it can be found that compared with the conventional Kalman filter, the ASMO achieves a smaller steady-state estimation error and has satisfactory robustness performance against 30% model mismatch.
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e-pub ahead of print date: 17 September 2019
Published date: 1 February 2020
Additional Information:
Funding Information:
Manuscript received May 24, 2019; revised July 4, 2019; accepted September 2, 2019. Date of publication September 17, 2019; date of current version January 14, 2020. This work was supported in part by a research contract from Wave Energy Scotland Control Systems Programme, in part by The Engineering and Physical Sciences Research Council (EPSRC) Grant “Launch and Recovery in Enhanced Sea States” under Grant EP/P023002/1, and in part by Newton Advanced Fellowship (NA160436). Paper no. TII-19-2018. (Corresponding author: Guang Li.) Y. Zhang is with the Queen Mary University of London, E1 4NS London, U.K. (e-mail:,yao.zhang@qmul.ac.uk).
Publisher Copyright:
© 2019 IEEE
Keywords:
M4, robustness, sliding-mode observer (SMO), wave energy converters, wave excitation force
Identifiers
Local EPrints ID: 472328
URI: http://eprints.soton.ac.uk/id/eprint/472328
ISSN: 1551-3203
PURE UUID: 4e77b34d-f3be-4b99-9c86-045c79b26c73
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Date deposited: 01 Dec 2022 17:41
Last modified: 18 Mar 2024 04:07
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Author:
Yao Zhang
Author:
Tianyi Zeng
Author:
Guang Li
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