Multivariable model predictive control of wind turbines in presence of actuator fault

Wind energy represents a promising renewable resource of electricity. Due to the higher complexity of modern wind turbines, advanced control becomes necessary. Multi input multi output control is known to be a good tool to account for coupling between the input and output variables, and is thus preferred in this work over decoupled single input single output controllers. Moreover, in order to account for the constraints on the inputs and outputs, model predictive control (MPC) is chosen. MPC also allows overcoming errors in the model parameters, which might occur due to faults in the actuators or sensors. A horizontal wind turbine is considered in this work, by manipulating the pitch angle and generator torque, in order to maintain producing the nominal power while minimizing loads on the generator system in the full load regime, i.e. at high rated wind speed. By tuning the weighting matrices of the controller, different weights can be attributed to the inputs and outputs. The controller was found to overcome faults in the actuator.