An improved fixed-time disturbance observer-based dynamic positioning control for unmanned surface vehicles under sparse false data injection attacks

This paper investigates the dynamic positioning (DP) control problem for unmanned surface vehicles (USVs) subjected to environmental disturbances, dynamics uncertainties and sparse false data injection (FDI) attacks, where an attacker can selectively manipulate signals within the control channels, with the potential to disrupt system stability and performance. First, a novel fixed-time sliding mode disturbance observer (FTSMDO) with a faster convergence rate, compared to previous studies, is designed to estimate lumped disturbance which includes the model uncertainty and the external disturbance. Second, a robust sliding mode controller is developed, incorporating an adaptive switching mechanism to ensure that the state errors converge to a small neighborhood of zero within a fixed time, even in the presence of sparse FDI attacks. The fixed-time stability of the closed-loop system is rigorously proven using Lyapunov theory. Finally, the efficacy of the proposed control strategy is validated through simulations utilizing a model of a floating production vessel.