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.