Event-triggered distributed disturbance rejection model predictive control for unmanned surface vehicles under lumped disturbances and input saturation

This paper proposes an event-triggered distributed disturbance rejection model predictive control (ET-DDRMPC) method for unmanned surface vehicles (USVs) affected by lumped disturbances and input saturation. A virtual leader is designed, and the corresponding desired trajectory will be obtained through a model predictive control (MPC) controller based on the error increment model. An uncertainty and disturbance estimator (UDE) is developed to estimate unknown nonlinear model uncertainties and external disturbances in each follower. Considering the reference tasks and lumped disturbances, a distributed disturbance rejection model predictive control (DDRMPC) controller is designed to achieve the USV formation, transforming the control problem into an optimization problem with input constraints and input increment constraints. Furthermore, a two-layer event-triggered mechanism (ETM) is devised: the outer ETM reduces the communication frequency between the virtual leader and the followers, while the inner ETM decreases the actuator update frequency of each follower USV, alleviating the communication burden. The recursive feasibility and stability of the proposed method are rigorously analyzed. Numerical simulations and comparisons are performed to demonstrate the effectiveness and superiority of the proposed strategy.