This thesis proposes a uniform multi-input, multi-output (MIMO) control framework for wind turbines using the robust linear parameter varying (LPV) design method. This framework is built on an LPV model of the wind turbine, which has a parametric dependence on the trim wind speed. It takes multiple objectives in different wind conditions into a systematic consideration. Therefore, existing results based on single-input, single-output (SISO) linear control design can be integrated together with stability and performance guarantees. The proposed design has a uniform structure that covers turbine operations in all wind conditions and provides better load reduction performance than the baseline controller. This MIMO control architecture can also be extended for active power control (APC) purposes. Therefore, the wind turbine is capable of providing ancillary services to maintain reliability of power grids. The control design in this thesis takes a robust LPV approach. Specifically, this thesis proposes a robust synthesis algorithm for LPV systems using the theory on integral quadratic constraints (IQCs). This algorithm is a coordinate-wise descent similar to the well-known DK iteration for $\mu$ synthesis. It alternates between an LPV synthesis step and an IQC analysis step. Both steps can be efficiently solved as semidefinite programs. It is shown that the proposed algorithm ensures that the robust performance is non-increasing at each iteration step. Therefore, this algorithm is used in this thesis to synthesize a robust LPV controller for wind turbines to provide APC. Robust performance of this controller has been verified using high fidelity simulations. Applications of this method will be various and not limited to wind turbines.