Parameter-varying Modeling and Nonlinear Model Predictive Control for Floating Offshore Wind Turbines

In this work, we present controllers with individual blade pitching (IBP) for a floating offshore wind turbine. Since the dynamics of the wind turbine depends on the rotor azimuth position ɸ, the equilibrium of the system also depends on ɸ. We derive reduced models for control design by two methods. One is linearization, and the other is trajectory linearization, which takes into account the dependence of the equilibrium on ɸ. The model considering the dependence of the equilibrium has a high model accuracy. However, we need to apply a nonlinear control method because the model includes nonlinearity. In this study, we use nonlinear model predictive control (NMPC). The simulation results show that the control performance improves by considering the variation of the equilibrium. In particular, NMPC considering the variation of the equilibrium can reduce the variations of stresses at the frequency of rotor rotation, whereas the conventional model predictive controller cannot.