Airborne sensors play an important role for the flight control system in the processes of flight status acquiring and control law solving of internal and external loops.In addition to increasing the hardware redundancy to improve the system reliability, it can also increase the analytical redundancy of the model to improve the system fault tolerance.In this paper, the flight control system is modeled and analyzed based on the aerodynamic parameters of UAV, and an optimal fault state estimator is designed.An improved residual detection method is proposed on the basis of Kalman-Bussy filter, which is used to online learn and estimate the fault state of the system.Furthermore, under the condition of joint voting based on periodic time and residual value, an adaptive reference model regulation law is designed to compare and modify the analytical model in real time, so as to reduce the influence of uncertainties caused by system interference.The simulation results show that the proposed method is feasible and effective.