An improved MPSP-based path-following control method for USV with input disturbances

This study proposes an improved model predictive static programming (MPSP) based path-following control method for unmanned surface vessel (USV) subject to input disturbances. The method addresses the challenges of accurate USV dynamics modeling, unpredictable maritime environments, and limited power and energy systems. A trajectory generator is designed to construct smooth reference trajectories, and the MPSP algorithm is adapted to handle path-following problems while considering state and input constraints. An event-triggered mechanism is introduced to reduce computational burden and conserve energy. Comparative simulations demonstrate the superiority of the proposed method over open-loop tracking and the original MPSP approach in terms of tracking accuracy, disturbance rejection, and overall control performance. The improved MPSP-based control method offers a robust and efficient solution for USV path-following tasks, ensuring accurate tracking even in the presence of environmental disturbances and system uncertainties.