Adaptive Fault-Tolerant Control of a Quadrotor Helicopter Based on Sliding Mode Control and Radial Basis Function Neural Network

In this paper, an adaptive fault-tolerant control strategy is proposed for a quadrotor helicopter in the presence of actuator faults and model uncertainties by integrating sliding mode control and radial basis function neural network. By assuming knowledge of the bounds on external disturbances, a baseline sliding mode control is first designed to achieve the desired system tracking performance and retain insensitive to disturbances. Then, regarding actuator faults and model uncertainties of the quadrotor helicopter, neural adaptive control schemes are constructed and incorporated into the baseline sliding mode control to deal with them. Finally, a series of simulation tests are conducted to validate the effectiveness of the proposed control strategy where a quadrotor helicopter is subject to inertial moment variations and different level of actuator faults. The capability of the proposed control strategy is confirmed and verified by the demonstrated results.