System modeling and identification of unmanned quad rotor air vehicle based on subspace and PEM

In order to achieve accurate control of unmanned quad rotor air vehicle, the system model is in need. In this paper, the system model was built under the condition of the small angle hypothesis. Then, we combined the subspace state space system identification method and prediction error method (PEM) to the system identification of quad rotor air vehicle. By simulation, the flight dynamics model of unmanned quad rotor air vehicle example was successfully identified. The results showed that the proposed method had the advantage of both subspace state space system identification method and PEM, and it was always convergent and numerically stable.