The spar-buoy floating wind turbine is one of the three main floating wind turbine concepts and one of the first to proceed to a full-scale prototype stage. Multiobjective linear state feedback controllers are implemented on the spar-buoy floating wind turbine with individual blade pitching (IBP). The spar-buoy's deep draft results in a low platform pitch and roll natural frequencies. The low-frequency pitch and roll modes interact with other low-frequency modes of the system (i.e., surge and sway, respectively). Therefore, the linear state-space model used for control design must include the surge and sway degrees of freedom. Furthermore, a low platform pitch natural frequency limits the effectiveness of IBP at regulating the platform pitch around the first tower fore-aft (FA) resonant frequency. Simulations using a high-fidelity model are carried out according to design load case 1.2 of the IEC-61400-3 standard for fatigue load testing under normal operating conditions. Simulation results relative to a gain-scheduled proportional-integral controller show that a multiobjective state feedback controller is able to reduce tower FA and side-side bending fatigue loads by an average of 9%. This improvement is mainly due to IBP despite its limited effectiveness around the first tower FA resonant frequency.

Pitching the individual blades of a horizontal-axis wind turbine allows control of asymmetric aerodynamic loads, which in turn influences structural loads in the nonrotating frame such as tower side-side bending. These loads are not easily controlled by traditional collective pitch algorithms. This paper presents the design of individual pitch control systems for implementation on the Controls Advanced Research Turbine (CART) in Colorado to verify controller performance for load attenuation. The control designs are based on linear time-periodic state-space models of the turbine and use optimal control methods for gain calculation. Comparisons are made between new individual pitch, new collective pitch, and baseline controller performance in both above rated and below rated wind conditions. Results from simulations show the potential of individual pitch to reduce tower side-side fatigue damage in above rated wind speeds (by 70% compared to baseline control) but with no improvement over collective pitch in below rated wind speeds. Fatigue load reductions in tower fore-aft, shaft torsion, and blade flap are also observed. From $13h$ of field testing, both collective and individual pitch controllers achieve a reduction in fatigue damage. However, the superior performance of individual pitch control observed in simulation was not verified by the field test results.

Performance of a model-based periodic gain controller for wind turbines is presented using Disturbance Accommodating Control (DAC) techniques to estimate fluctuating wind disturbances. The control objective is to regulate rotor speed at above-rated wind speeds while mitigating cyclic blade root loads. Actuation is via individual blade pitch, and sensors are limited to rotor angle and speed. The modeled turbine is a two-bladed, downwind machine with simple blade and tower flexibility having four degrees of freedom. Comparisons are made to a time-invariant DAC controller and to a proportional-integral-derivative (PID) design. Simulations are performed using a fluctuating wind input and a nonlinear turbine model. Results indicate that the state-space control designs are effective in reducing blade loads without a sacrifice in speed regulation. The periodic controller shows the most potential because it uses a time-varying turbine model to estimate unmeasured states. The use of additional sensors to help reconstruct the blade flap rate can significantly improve the level of load attenuation, as witnessed in full-state feedback results.