In recent years, intending to increase the nominal power generation capacity of wind turbines, the height of the tower and the size of the turbine (especially the rotor diameter and the length of the blades) have been increased. This structural enlargement results in greater flexibility of the components and an increment in the system's vibrations, which produces high tensions in those components causing a reduction in their useful life. In this regard, the wind turbine control becomes crucial since it helps to reduce the structural loads.

In this context, model predictive control (MPC) is an advanced control technique that has been used for a long time in the industry.

This Dissertation proposes an MPC controller that uses a single internal linear model (SMPC), which facilitates its practical implementation. This controller aim to reduce the structural load on the transmission train and/or the wind turbine rotor.

Thus, this Dissertation presents the design of an SMPC, its internal model, cost function, and a stability test based on Lyapunov theory. The design of two versions of the new controller is also described, which does not consider input perturbation preview in their design. Likewise, this Dissertation presents the third version of the designed SMPC, in which, through the use of a LIDAR sensor, the incoming disturbance is calculated in advance.