In below-rated wind conditions, a wind turbine operates to maximize the amount of available power harvested from the wind and is said to be operating in region 2. In above-rated wind conditions, where regulation is the main objective to prevent over power and speed faults and to mitigate loads, the turbine is said to be in region 3. There is no standard method for operation at the boundary of the two regions and transitions between them can be problematic. In this study, we use iterative learning control to determine the control actuation necessary to accurately track idealized candidate trajectories during the transition between regions 2 and 3. The amount of control actuation required to track a transition trajectory and the ability to do so with minimal collateral loading determines which trajectory is most amenable for a given turbine. Trajectories are also graded by the average power produced during transition since they take the turbine off of the optimal power point.