We formulate a controller for wind turbines that has three main characteristics. First, it optimizes profit by balancing revenue from power generation with cost. Second, cost includes the effects of cyclic fatigue that, departing from most of the existing literature on control, is rigorously accounted for by an exact cycle counting on receding horizons. Third, it uses a model capable of learning and improving its performance based on measured or synthetic data.