Control of small two-body heaving wave energy converters for ocean measurement applications
Control of small two-body heaving wave energy converters for ocean measurement applications
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DOI：
10.1016/j.renene.2018.08.004
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发表时间：
2019-03
期刊：
影响因子：
8.7
通讯作者：
O. Abdelkhalik;Shangyan Zou
中科院分区：
文献类型：
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作者：
O. Abdelkhalik;Shangyan Zou
携带科学设备的浮标通常需要持续的电源来运行这些设备。这些浮标可以配备有致动器，并被控制以从浮标的起伏运动中获取动力。两体波能转换器可以被设计成使得浮标升高以收集能量，而第二（下部）体承载科学设备。本文提出了一种控制方法，这种类型的两体波能转换器。这种控制方法是一种多共振控制，试图最大化从浮标（上身）收集的能量。在该模型中，致动器连接到两个主体。然而，要求下部主体具有最小的升沉运动。所提出的多谐振控制利用浮标位置的测量。估计所测量的浮标位置的频率，沿着这些频率的运动幅度，并用于反馈控制。使用两种方法进行估计;第一种使用线性卡尔曼滤波器，而第二种使用扩展卡尔曼滤波器。提出了一种适用于多谐振控制的运动和驱动限制处理方法。文中给出了各种数值模拟结果。仿真结果表明，线性卡尔曼滤波估计方法是更强大的和计算效率相比，扩展卡尔曼滤波。
Buoys carrying scientific equipment usually need continuous power supply for the operation of these equipments. These buoys can be equipped with actuators and controlled to harvest power from the heaving motion of the buoy. A two-body wave energy converter can be designed such that the buoy heaves to harvest energy while the second (lower) body carries the science equipments. This paper presents a control approach for this type of two-body wave energy converter. This control approach is a multi resonant control that attempts to maximize the harvested energy from the buoy (upper body). In this model, the actuator is attached to both bodies. The lower body however is required to have minimal heave motion. The proposed multi resonant control utilizes measurements of the buoy position. The frequencies of the measured buoy position are estimated, along with the motion amplitudes of these frequencies, and used for feedback control. Estimation is carried out using two approaches; the first uses a linear Kalman filter while the second uses an extended Kalman filter. A new method for handling the motion and actuation limitations, suitable for the multi resonant control, is proposed. Various numerical simulation results are presented in the paper. Simulation results show that the linear Kalman filter estimation approach is more robust and computationally efficient compared to the extended Kalman filter.