Disturbance rejection event-triggered robust nonlinear model predictive control for underactuated unmanned surface vehicle against DoS attacks without velocity measurements.

Abstract

This paper presents a disturbance rejection event-triggered nonlinear model predictive control (DR-ETNMPC) method for underactuated unmanned surface vehicle (USV) subject to denial-of-service (DoS) attacks and lacking velocity measurements. A nonlinear extended state observer (NESO) is employed to estimate both unknown velocities and lumped disturbances, while a disturbance rejection nonlinear model predictive controller (DRNMPC) is designed to enforce actuator saturation constraints. To reduce computational load of the DRNMPC, an event-triggered mechanism is introduced, and a DoS attack defense mechanism is introduced to guarantee that the USV maintains high-precision tracking performance under DoS attacks. Rigorous analysis is conducted to ensure recursive feasibility and closed-loop stability. Simulation results verify the method's effectiveness and superiority, demonstrating notable improvements in both control precision and computational efficiency.