In this paper a small scale wind generator based on a permanent magnet synchronous machine (PMSM) and associated with an indirect maximum power point tracking (MPPT) algorithm is proposed. Choosing an energy conversion active structure and a sensorless PMSM, to control the system, a speed estimator is required. Facing to other methods, the extended Kalman filter (EKF) model-based estimator allows sensorless drive control in a wide speed range and estimates the rotation speed with a rapid response. The EKF parameters tuning is solved by introducing an adaptive method, i.e. adaptive-tuning EKF. This adaptive estimation approach is innovative by using a covariance matching technique. The experimental results prove that the proposed method is technically feasible with good performances within some limits.