IFAC-PapersOnLine · 2019 · 23 citations · 12 references
EngineeringAerospace EngineeringRobotics EngineeringFault ToleranceFault-tolerant SystemsUnmanned Aircraft SystemsAdaptive ControlAircraft ControlAttitude ControlFault DetectionFault DiagnosisFault-tolerant ControlFault Detection In Aerial VehiclesFault Detection In Control SystemsLyapunov Stability TheoryObserver Design For FaultsObserver-based Fault-tolerant ControlRadial Basis Function NetworksRobust Observer DesignUnmanned Aerial Vehicle Control
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.
12