In this paper, it is proposed a technique to optimize the power generated by a small scale wind turbine, by having no wind speed measurement and uncertain knowledge of the power coefficient curve characteristic. First, a Kalman-like observer is used for estimating the power coefficient characteristic, which is then used in a nonlinear control strategy for the electrical generator that secures power maximization. Then, the uncertain power coefficient function is adjusted with a Recursive Least-Square algorithm that uses the estimate of the power coefficient as reliable information. Finally, from the adjusted power coefficient polynomial is computed the optimal electrical generator speed reference that leads the system to operate near the theoretical optimal power. This methodology is illustrated on a simulated example and compared with a case when the wind speed is measured.