Nussbaum-Based Adaptive Neural Fractional-Order Sliding-Mode Fault-Tolerant Control of Unmanned Aerial Vehicles

To realize the tracking control of fixed-wing unmanned aerial vehicle (UAV) with actuator fault, an adaptive neural network (NN) fractional-order (FO) sliding-mode fault-tolerant control (FTC) method is proposed. The Nussbaum function is employed to handle the loss-of-effectiveness fault, and the adaptive method is combined with radial basis function neural network (RBFNN) to learn the bias fault. Furthermore, FO sliding-mode mechanism is designed to heighten the robustness. The Lyapunov method is employed to prove the stability of FTC system. Finally, simulation results are provided to show the effectiveness of the designed control method.