A Sensitivity Analysis of Wave Energy Converter Model Predictive Control Systems With Wave Excitation Force Estimation and Prediction

Understanding the sensitivity of energy-maximizing control for wave energy converters (WECs), to various model errors, is crucial for application. Many advanced WEC controllers, especially model predictive control (MPC)-like controllers, require estimation and prediction of wave excitation force (WEF). However, previous studies only focus on the controller in isolation, without considering the error coupling effects when a complete estimation-prediction loop is involved. In this study, it is revealed through numerical analysis that the complete MPC system has sensitivity behavior completely different from the isolated MPC; under certain model errors, the system can become particularly unpredictable, exhibiting potential instability and self-locking phenomena, which cannot be observed from the examination of control sensitivity alone. Meanwhile, different tuning options for the WEF estimator and predictor are examined, where the accuracy-robustness tradeoff is shown to be critical for performance amelioration under errors. Based on the analysis, this study challenges the widely assumed “separation principle” of WEF estimation/prediction and WEC control, highlights the importance of incorporating a complete estimation-prediction loop in sensitivity examination, and draws practical guidelines for WEC control application.

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Publication Details

Journal
IEEE Transactions on Control Systems Technology
Published
2024-09-30
DOI
https://doi.org/10.1109/tcst.2024.3456689
Citations
5
Primary Topic
Wave and Wind Energy Systems
Type
article
Field-Weighted Citation Impact
1.68

Funders

Controls
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article

A Sensitivity Analysis of Wave Energy Converter Model Predictive Control Systems With Wave Excitation Force Estimation and Prediction

Zechuan Lin, Xuanrui Huang, John Vincent Ringwood, Xi Xiao
5 citations
IEEE Transactions on Control Systems Technology
Wave and Wind Energy Systems
1.68
article

A Sensitivity Analysis of Wave Energy Converter Model Predictive Control Systems With Wave Excitation Force Estimation and Prediction

Zechuan Lin, Xuanrui Huang, John Vincent Ringwood, Xi Xiao
article en
5 citations

Abstract

Understanding the sensitivity of energy-maximizing control for wave energy converters (WECs), to various model errors, is crucial for application. Many advanced WEC controllers, especially model predictive control (MPC)-like controllers, require estimation and prediction of wave excitation force (WEF). However, previous studies only focus on the controller in isolation, without considering the error coupling effects when a complete estimation-prediction loop is involved. In this study, it is revealed through numerical analysis that the complete MPC system has sensitivity behavior completely different from the isolated MPC; under certain model errors, the system can become particularly unpredictable, exhibiting potential instability and self-locking phenomena, which cannot be observed from the examination of control sensitivity alone. Meanwhile, different tuning options for the WEF estimator and predictor are examined, where the accuracy-robustness tradeoff is shown to be critical for performance amelioration under errors. Based on the analysis, this study challenges the widely assumed “separation principle” of WEF estimation/prediction and WEC control, highlights the importance of incorporating a complete estimation-prediction loop in sensitivity examination, and draws practical guidelines for WEC control application.

IEEE Transactions on Control Systems TechnologyVol. 33(1)
National University of Ireland, Maynooth (IE), Tsinghua University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 17%
Wave and Wind Energy Systems
1.68
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