Horizontal Axis Wind Turbine (HAWT) rotor is a system whose components are particularly exposed to fatigue damage, due to non-uniform winds and the rotating nature of the rotor. Individual Pitch Control (IPC) can help alleviating the fatigue loads on the rotor blades by rotating the blades independently from each other on their longitudinal axis. However, reducing the blades fatigue damage is often compensated by an increase in pitch activity, damaging the blade pitch actuators. An IPC regulator must thus optimize a trade-off between the fatigue damage of the blades and blade pitch actuators. This paper presents the derivation and implementation of a fatigue-oriented adaptive Model Predictive Control (MPC) IPC regulator using a data-driven fatigue-oriented cost function. This MPC allows to efficiently optimize the IPC fatigue trade-off and significantly reduce the expectancy of an HAWT rotor economic fatigue cost, compared to a finely tuned non-adaptive MPC. The methodology used for the derivation of the presented MPC allows to efficiently reduce an economic fatigue cost, while limiting the sensitivity to controller tuning.

水平轴风力涡轮机（HAWT）转子是一种系统，由于风的不均匀性和转子的旋转特性，其组件特别容易遭受疲劳损坏。单独的变桨控制（IPC）可通过在叶片的纵轴上彼此独立地旋转来帮助减轻转子叶片上的疲劳负荷。但是，减少叶片疲劳损伤通常可以通过增加螺距活动来补偿，从而损坏叶片螺距致动器。因此，IPC调节器必须优化叶片和叶片变桨致动器的疲劳损伤之间的权衡。本文介绍了基于数据驱动的疲劳导向成本函数的疲劳导向自适应模型预测控制（MPC）IPC调节器的推导和实现。与经过微调的非自适应MPC相比，该MPC可以有效地优化IPC疲劳折衷，并显着降低HAWT转子经济疲劳成本的预期。用于推导所提出的MPC的方法允许有效地降低经济上的疲劳成本，同时限制了控制器调整的敏感性。