In this study, we address the issue of real-time energy-maximising control for wave energy converters (WECs), by proposing a receding-horizon optimal control framework based on the concept of a moment . This approach is achieved by extending the so-called moment-based framework, recently published in the WEC literature, to effectively solve the associated optimal control problem within a finite time-horizon, allowing for real-time performance, and a straightforward inclusion of the wave excitation force $\mathcal {F}_e$ estimation and forecasting requirements, which are intrinsic to the wave energy control application. We present a case study, based on a CorPower-like device, subject to both state and input constraints. We show that the proposed strategy can perform almost identically to the ideal performance case, where full knowledge of $\mathcal {F}_e$ over the time-horizon is assumed available. Moreover, a sensitivity analysis is provided, addressing the impact of wave excitation force estimation and forecasting errors in the computation of the moment-based control input. Two main conclusions can be drawn from this analysis: Forecasting mismatch has a negligible impact on the overall performance of the strategy, while potential differences arising from estimating $\mathcal {F}_e$ , in particular, phase errors, can substantially impact total energy absorption.

中文翻译：

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基于矩的波浪能系统的后视能量最大化最优控制

在这项研究中，我们提出了一种基于a的概念的水平后退最优控制框架，从而解决了波浪能转换器（WEC）的实时最大能量控制问题。 时刻 。这种方法是通过扩展所谓的基于时刻 框架，最近在WEC文献中发表，可以有效地解决有限时间范围内的相关最佳控制问题，从而实现实时性能并直接包含波浪激励力 $ \数学{F} _e $估计和预报要求，这是波浪能控制应用程序固有的。我们基于类似CorPower的设备提出了一个案例研究，该案例受状态和输入约束的约束。我们证明了所提出的策略几乎可以与理想绩效情况相同，在这种情况下，$ \数学{F} _e $假设时间跨度可用。此外，提供了灵敏度分析，解决了基于矩的控制输入计算中的波激励力估计和预测误差的影响。可以从该分析得出两个主要结论：预测失配对策略的整体绩效影响可忽略不计，而估计带来的潜在差异$ \数学{F} _e $ 尤其是相位误差会严重影响总能量吸收。