Trajectory tracking of USV with disturbance observer and predictive compensator under network attacks and network delays

This study addresses the trajectory tracking problem of an unmanned surface vehicle (USV) under remote control mode, which is subject to network delays, denial of service (DoS) attacks, unknown time-varying environmental disturbances, and model uncertainties. A trajectory tracking strategy incorporating a nonlinear disturbance observer (NDO) and predictive compensators is proposed. First, an NDO is designed to compensate for the effects of model uncertainties and environmental disturbances on the USV. Second, network delays and DoS attacks are mathematically modeled. A control information predictive compensator (CIPC) and a state information predictive compensator (SIPC) based on feedforward differentiation are designed to compensate for the adverse effects of DoS attacks and network delays on ship-to-shore communication. Subsequently, integrating the NDO, a control law with a robust switching term is designed based on the second method of Lyapunov to achieve USV trajectory tracking, where the robust switching term compensates for the estimation errors of the NDO regarding environmental disturbances and uncertain models. The convergence of error signals is proven using Lyapunov theory. Finally, numerical simulation experiments are conducted on a ferry equipped with two full rotation thrusters to validate the effectiveness of the proposed control strategy.