  This work presents a combined feedforward-feedback wake redirection framework
for wind farm control. The FLORIS wake model, a control-oriented steady-state
wake model is used to calculate optimal yaw angles for a given wind farm layout
and atmospheric condition. The optimal yaw angles, which maximize the total
power output, are applied to the wind farm. Further, the lidar-based
closed-loop wake redirection concept is used to realize a local feedback on
turbine level. The wake center is estimated from lidar measurements \unit[3]{D}
downwind of the wind turbines. The dynamical feedback controllers support the
feedforward controller and reject disturbances and adapt to model
uncertainties. Altogether, the total framework is presented and applied to a
nine turbine wind farm test case. In a high fidelity simulation study the
concept shows promising results and an increase in total energy production
compared to the baseline case and the feedforward-only case.
