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A generic linear non-causal optimal control framework integrated with wave excitation force prediction for multi-mode wave energy converters with application to M4

机译:一种具有应用于M4的多模波能转换器的波激励力预测的通用线性非因果最优控制框架

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摘要

The multi-float multi-mode wave energy converter (M-WEC) M4 has essentially linear hydrodynamics characteristics in operational and even extreme waves. This is in contrast to point-absorber and most raft-type devices where nonlinear effects and associated losses are significant. The control problem now involves a large number of degrees of freedom. Energy maximizing control of wave energy converters (WECs) is a non-causal control problem. This paper aims to propose a complete self-contained non-causal optimal control framework by combining a linear non-causal optimal control (LNOC) algorithm with an autoregressive (AR) model as the wave excitation force predictor and a Kalman Filter with random walk wave model (KFRW) as the wave excitation force estimator. The efficacy of the proposed framework together with its enabling components is demonstrated numerically using irregular waves. The proposed framework has low computational load, which enables its real-time implementation on standard computational hardware. Furthermore, the wave force prediction does not require deployment and maintenance of expensive hardware, which helps to reduce the unit cost of the generated electricity.
机译:多浮点多模式波能量转换器(M-WEC)M4在操作甚至极端波的基本上具有线性的流体动力学特性。这与点吸收器和大多数筏式设备形成鲜明对比,其中非线性效应和相关损失是显着的。控制问题现在涉及大量的自由度。波能转换器(WECS)的能量最大化控制是一个非因果控制问题。本文旨在通过将具有自回归(AR)模型的线性非因果最佳控制(LNOC)算法与随机步行波的波浪激发力预测器和卡尔曼滤波器组合,提出完整的自包含的非因果算法模型(KFRW)作为波激励力估计器。所提出的框架与其启动组件一起的功效在数值上使用不规则波进行了数值展示。所提出的框架具有低计算负载,这使得其在标准计算硬件上的实时实现。此外,波力预测不需要部署和维护昂贵的硬件,这有助于降低所产生的电力的单位成本。

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