Research on the Control Method for Remotely Operated Vehicle Active Docking with Autonomous Underwater Vehicles Based on GFSMO-NMPC

This study proposes a control method for Remotely Operated Vehicles (ROVs) to actively dock with AUVs, to address the limitations of traditional docking and recovery schemes for Autonomous Underwater Vehicles (AUVs), such as restricted maneuverability and external disturbances. Firstly, a process and control strategy for ROV active docking with AUVs is designed, improving docking safety. Secondly, a Nonlinear Model Predictive Controller (NMPC) based on a Gaussian Function Sliding Mode Observer (GFSMO) compensation is designed for the ROV, generating smooth control inputs to achieve high-precision trajectory tracking and real-time docking. Finally, a joint simulation experiment is established through WEBOTS 2023a and MATLAB 2023a, verifying the superiority and feasibility of the designed controller and the proposed method. After parameter optimization, the simulation results show the method proposed in this study has a 90% success rate in 10 docking experiments under different disturbances.