Fuzzy adaptive super-twisting formation control for multiple fixed-wing UAVs: A barrier Lyapunov function approach with asymmetric time-varying state constraints

This paper proposes a novel fuzzy adaptive super-twisting formation control framework for fixed-wing unmanned aerial vehicles subject to asymmetric time-varying state constraints and multisource uncertainties. A virtual leader-based strategy is first introduced to transform the formation consensus problem into a trajectory-tracking task. A robust nonlinear composite disturbance observer is then developed to estimate lumped disturbances and their derivatives, while a fuzzy logic system approximates unknown nonlinear dynamics. To handle asymmetric constraints, an innovative asymmetric time-varying tangent-type barrier Lyapunov function is proposed, ensuring the boundedness of all closed-loop signals. The integration of an adaptive super-twisting control algorithm further enhances transient performance and chattering suppression. Lyapunov stability analysis proves the uniform ultimate boundedness of tracking errors. Comparative simulations demonstrate that the proposed method achieves a faster convergence rate with reduced tracking errors compared to conventional methods, validating its superiority in robustness and constraint satisfaction.