The ongoing increase in size of modern wind turbines creates the demand of better control algorithms to counteract the increased loads acting on them. Individual blade pitch control (IPC) algorithms to alleviate blade loads are becoming a crucial part of current wind turbine control systems. The state-of-the-art individual blade pitch load reduction controller mostly relies on multiple single-input single-output (SISO) designs. This approach, however, constrains the achievable bandwidth of the controller as relevant couplings in the dynamics are ignored. These couplings become more pronounced for bigger turbines. Model-based multiple-input multiple output (MIMO) control designs can be used to account for these couplings and hence reduce loads for future, larger turbines. In this article we present the results of an intensive field test campaign of an $H_{\infty }$-design based MIMO IPC. This controller is designed for and tested on the utility-scale 2.5 MW Clipper Liberty research turbine operated by the University of Minnesota. The article guides the reader through the turbine’s open loop dynamics, the IPC design and the relevant implementation steps on the turbine. Finally, the developed $H_{\infty }$-based IPC is compared using experimental field data against no IPC (collective blade pitch control) and a classical IPC based on decoupled SISO loops.

现代风力涡轮机尺寸的不断增加产生了对更好的控制算法的需求，以抵消作用在其上的增加的负载。减轻叶片负载的独立叶片变桨控制（IPC）算法正成为当前风力涡轮机控制系统的关键部分。最新的单个叶片变桨负载减小控制器主要依靠多个单输入单输出（SISO）设计。但是，由于忽略了动力学中的相关耦合，因此这种方法会限制控制器的可实现带宽。这些联轴器对于更大的涡轮机变得更加明显。基于模型的多输入多输出（MIMO）控制设计可用于解决这些耦合问题，从而减少未来大型涡轮机的负荷。$H_{\infty }$设计的MIMO IPC。该控制器专为明尼苏达大学（University of Minnesota）实用型2.5兆瓦Clipper Liberty研究型涡轮机设计并经过测试。本文通过涡轮机的开环动力学，IPC设计以及涡轮机上的相关实施步骤来指导读者。最后，发达$H_{\infty }$使用实验现场数据将基于IPC的IPC与无IPC（叶片桨距控制）和基于解耦SISO回路的经典IPC进行比较。