LAUSR

Abstract A robust adaptive observer combined with radial basis function neural network (RBFNN) is designed for the unmanned aerial vehicles (UAVs) fault-detection system is proposed in this paper. Firstly, the fault dynamics model with unknown disturbance of the unmanned aerial vehicle’s attitude system is established, and a robust adaptive observer combined with radial basis function neural network is designed for the vehicle’s fault-detection, then, the detected fault combined with a robust controller is applied to design the fault-tolerant controller. In the end, the stability and effective of the fault detection and tolerant system is proved by Lyapunov theory and simulation.