Active fault-tolerant control for a quadrotor helicopter against actuator faults and model uncertainties

This paper proposes an active fault-tolerant control strategy for a quadrotor helicopter against actuator faults and model uncertainties while explicitly considering fault estimation errors based on adaptive sliding mode control and recurrent neural networks. Firstly, a novel adaptive sliding mode control is proposed. In virtue of the proposed adaptive schemes, the system tracking performance can be guaranteed in the presence of model uncertainties without stimulating control chattering. Then, due to the fact that model-based fault estimation schemes may fail to correctly estimate fault magnitudes in the presence of model uncertainties, a fault estimation scheme is proposed by designing a parallel bank of recurrent neural networks. With the trained networks, the severity of actuator faults can be precisely estimated. Finally, by synthesizing the proposed fault estimation scheme with the developed adaptive sliding mode control, an active fault-tolerant control mechanism is established. Moreover, the issue of actuator fault estimation error is explicitly considered and compensated by the proposed adaptive sliding mode control. The effectiveness of the proposed active fault-tolerant control strategy is validated through real experiments based on a quadrotor helicopter subject to actuator faults and model uncertainties. Its advantages are demonstrated in comparison with a model-based fault estimator and a conventional adaptive sliding mode control.