This paper aims to resolve the distributed containment control problem for multi-quadrotor unmanned aerial vehicle (QUAV) formations operating under adverse conditions. The primary objective is to drive follower QUAVs into the convex hull formed by leaders while effectively handling the composite influence of unknown nonlinear dynamics, external disturbances, and time-varying actuator faults.
A distributed adaptive fault-tolerant control strategy is proposed based on the backstepping technique and neural network (NN) approximation. Radial basis function NNs are used to identify unknown model nonlinearities without requiring precise structural knowledge. An adaptive fault-compensation mechanism is seamlessly integrated into the controller design to counteract actuator degradation. By leveraging Lyapunov stability theory, it is theoretically proven that the proposed scheme ensures all closed-loop signals are uniformly ultimately bounded and the containment errors converge to an adjustable residual set.
The efficacy of the proposed strategy is validated through numerical simulation. The results indicate that the followers can successfully maintain the desired formation structure and achieve containment even when actuators under fault conditions. The adaptive mechanism effectively suppresses the impact of uncertainties, ensuring stable and reliable flight maneuvers.
The distinct contribution of this work lies in the unified framework that tackles the coupling effects of nonlinear uncertainties and multiple actuator faults for underactuated QUAV systems.
