Excitation force estimation and forecasting for wave energy applications

Garcia-Abril, Marina; Paparella, Francesco; Ringwood, John V.

doi:10.1016/j.ifacol.2017.08.2499

Cited by 39 publications

(27 citation statements)

References 13 publications

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“…3. The states q and its first derivativeq can be directly measured, and the state corresponding to the radiation force r which does not have physical meanings can be estimated by a KF [8]. By using the control input, the state q, its derivativeq and the state r, the proposed ASMO estimates wave excitation force in realtime.…”

Section: Adaptive Sliding-mode Observer For Wave Excitation Forcmentioning

confidence: 99%

“…The Kalman Filter (KF) was employed for wave excitation force estimation problem in recent years [7], [8] and was proven to be effective to achieve real-time estimations. While there is model mismatch between the state-space model and the original hydrodynamic model, which is caused by wave force approximations, unmodelled wave forces and environmental uncertainties, etc.…”

Section: Introductionmentioning

confidence: 99%

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Robust Excitation Force Estimation and Prediction for Wave Energy Converter M4 Based on Adaptive Sliding-Mode Observer

Zhang

Zeng

2020

IEEE Trans. Ind. Inf.

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The wave excitation force estimation and prediction plays an important role in improving the performance of causal and non-causal controllers for wave energy converters (WECs). This paper proposes a robust adaptive sliding-mode observer (ASMO) to estimate the wave excitation force subject to unknown disturbances and parametric uncertainties for a multi-motion multi-float 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 non-causal controller requiring future excitation force. From the comparison based on a realistic sea wave gathered from Cornwall, UK, 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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Section: Adaptive Sliding-mode Observer For Wave Excitation Forcmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Excitation Force Estimation and Prediction for Wave Energy Converter M4 Based on Adaptive Sliding-Mode Observer

Zhang

Zeng

2020

IEEE Trans. Ind. Inf.

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“…F ex is described in the last 2nf rows of A using a harmonic oscillator model, based on f frequencies, since F ex is, in general, oscillatory. For further details, refer to [13], [14]. Thus, the system matrix A ∈ R (1+f )2n×(1+f )2n , for an array of n bodies, based on f frequencies, is defined as…”

Section: Excitation Force Estimationmentioning

confidence: 99%

“…whereF ex k|k−1 is the predicted value of F ex at instant k from data up to, and including, k−1, h is the order of the forecasting model, φ i are the autoregressive coefficients. Equation (14) can be written more concisely as…”

Section: Excitation Force Forecastingmentioning

confidence: 99%

“…Regarding prediction, a number of studies have focussed on the prediction of future wave elevation, rather than on the prediction of future F ex [7]. However, combined estimation/forecasting of F ex has been addressed [13], [14]. The main novelty in this paper is the consideration of a WEC array, where the wave field is complicated by the presence of diffracted and radiated waves from the array WECs.…”

Section: Introductionmentioning

confidence: 99%

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Estimation and Forecasting of Excitation Force for Arrays of Wave Energy Devices

Peña-Sanchez

Garcia-Abril

Paparella

et al. 2018

IEEE Trans. Sustain. Energy

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To maximise energy conversion, real-time control of a Wave Energy Converter (WEC) requires knowledge of the present and future excitation force (Fex) acting on the device, which is a non-measurable quantity. The problem of estimation and forecasting of Fex becomes more challenging when arrays of WECs are considered, due to the hydrodynamic interactions in the array. In this paper, a global Fex estimator for a complete WEC array is developed and compared to a set of independent estimators which utilise information local only to each device. A significant question is whether the array of measurements is sufficient to compensate for the greater complexity of the wave field, compared to the isolated body case. The paper shows that the global estimator is always more accurate than the independent estimator, improving up to 45% the estimation accuracy of the independent estimator. Regarding prediction, two different Fex forecasters for a WEC array are compared: a global forecaster, utilising Fex estimates from the full set of array devices, and an independent forecaster, utilising only a local Fex estimate. We demonstrate that the global forecaster achieves more accurate results, not only compared to the independent forecaster, but also compared to the isolated body case.

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