Nonlinear Robust Fault-Tolerant Tracking Control of a Tri-Rotor UAV against Actuator's Abnormal Behavior

In this paper, a new nonlinear robust fault-tolerant tracking control method is proposed for a tri-rotor unmanned aerial vehicle (UAV) under unknown abnormal actuator behaviors together with unknown external disturbances. The actuator anomalies are modeled as time-varying multiplicative parameters to improve the model accuracy. The control system is decoupled into two parts, including the inner-loop attitude control and the outer-loop position control. The radial basis function neural network (RBFNN) is utilized in the outer loop to estimate the actuator anomalies and external disturbances, and then the state feedback controller is employed for the position tracking of the UAV. Then, the robust integral of the signum of the error (RISE) controller is designed for the inner loop to compensate for actuator anomalies and external disturbances. The composite stability of the closed-loop system and the asymptotical tracking performance are proved via a Lyapunov-based stability analysis. Numerical simulations based on the proposed fault tolerant control (FTC) scheme as well as the comparison results with a sliding mode-based FTC method validate the effectiveness and better performance of the proposed control design.