Robust Lyapunov Model Predictive Path Tracking Control for Autonomous Electric Sailboats Based on Disturbance Predictor

Autonomous electric sailboats (UESs), fully powered by wind energy, have board applications in ocean observation. However, the complex and unpredictable marine environment introduces significant disturbances and uncertainties into their motion control. The inherent robustness of standard model predictive control (MPC) cannot meet the requirement of stability under large disturbances. To address these challenges, a robust Lyapunov MPC (RLMPC) based on disturbance predictor (DP) is proposed. First, a DP is designed to forecast future disturbance behavior, and the predicted disturbances are incorporated into the nominal model of MPC, enhancing its ability to suppress time-varying disturbances. Additionally, the contraction constraint of the Lyapunov MPC (LMPC) optimization problem is formulated using an auxiliary control law based on the DP, ensuring closed-loop stability and improving control performance. Actuator saturation and incremental constraints are also considered. The cooperative path tracking strategy of sail and rudder based on DP-RLMPC not only ensures the sailing speed but also improves the path tracking accuracy. Finally, the effectiveness and robustness of the proposed algorithm are validated through simulations of UES operating in a complex marine environment and are compared with other advanced control strategies.