An Improved Model Predictive Control for Path-Following of USV Based on Global Course Constraint and Event-Triggered Mechanism
Baigang Zhao, Xianku Zhang, Cailei Liang, Xu Han
Abstract
In this work we propose a solution to the Unmanned Surface Vessels (USV) path-following problem by suggesting an improved model predictive control (MPC) based on global course constraint (GCC) and event-triggered mechanism (ETM). The designed GCC guidance law incorporates the LOS concept and overcomes its lack of reference signal near the waypoint. The developed MPC controller involves an ETM that ultimately optimizes the deviation according to its prediction ability and effect on energy saving. We challenge our model against current methods on the evaluation platform vessel “Yukun” of Dalian Maritime University and demonstrate the effectiveness and superiority of the suggested path-following algorithm over existing methods.