## 2 Background
### Lidar-Assisted Control Strategies  
The study of LAC began in earnest with the 2005 simulation-based investigation of blade pitch control for rotor speed regulation and blade load reduction presented by [PERSON] et al. (2011). Since then, LAC strategies have been explored using all three main types of wind turbine control actuation: yaw control, generator torque control, and blade pitch control. Furthermore, the use of lidar measurements for control has been investigated for both below-rated operation, particularly for optimizing power capture, as well as operation in above-rated wind speeds, where the objective is to regulate rotor speed and minimize structural loads. In the below-rated control region, both lidar-assisted yaw control and generator torque control have been investigated. Traditionally, yaw control is performed using wind direction measurements from a nacelle wind vane. However, improper calibration and flow disturbance behind the rotor can produce inaccurate wind vane measurements and rotor misalignment. Field tests performed by [PERSON] et al. (2011) show that a bias in the wind vane measurements can be detected and removed using measurements from a nacelle lidar, leading to an improvement in energy capture. [PERSON] et al. (2012) discuss yaw control experiments where information from the wind vane is completely replaced by more accurate lidar measurements, similarly resulting in greater energy capture. However, several authors argue that most of the performance increase from full-time lidar-assisted yaw control could likely be achieved by simply removing the wind vane bias, which could be accomplished with a one-time lidar-based wind vane calibration ([PERSON] et al., 2011; [PERSON] et al., 2013; [PERSON] et al., 2014). During below-rated operation, the primary purpose of generator torque control is to regulate rotor speed. For a subset of the below-rated control region, the objective is traditionally to maintain the tip-speed ratio of the rotor at its optimal value in order to maximize power capture. The use of lidar preview measurements to improve optimal tip-speed ratio regulation via generator torque control has been shown to provide a small increase in energy capture ([PERSON] et al., 2013; [PERSON] et al., 2014; [PERSON] et al., 2015). However, as observedby [PERSON] et al. (2013) and [PERSON] et al. (2016), the large generator torque fluctuations and drivetrain loads that result from this control strategy likely outweigh the modest benefits. Blade pitch control has been recognized as one of the more promising types of LAC because of the significant rotor speed regulation improvement as well as structural load reduction that can be achieved. Both collective pitch control, requiring estimates of the \"rotor effective wind speed\" (e.g., rotor average wind speed) ([PERSON] et al., 2012; [PERSON] et al., 2013; [PERSON] et al., 2013), and individual pitch control (IPC), in which each blade is controlled differently to account for spatial variations in the wind field ([PERSON] et al., 2012; [PERSON] et al., 2013; [PERSON] et al., 2014; [PERSON] et al., 2015), have been investigated. By mitigating the effect of spatially-varying wind speeds, using lidar measurements of either rotor effective quantities like wind shear or wind speeds local to the individual blades, IPC has the advantage of reducing blade loads as well as non-rotating loads transferred to the drivetrain and turbine structure beyond what can be achieved with collective pitch control. Note that, while most lidar-assisted IPC controller designs only use measurements of the wind _speed_ variations over the rotor area, [PERSON] et al. (2013) have recently proposed a lidar-assisted IPC controller that mitigates the impact of yaw misalignment and vertical inflow in addition to wind shear on blade loads.