Optimization of Trajectory Generation and Tracking Control Method for Autonomous Underwater Docking

Abstract

This study proposes a receding horizon optimization-based docking control method to address the autonomy and safety challenge of underwater docking between manned submersibles and unmanned vehicles, facilitating the integration of docking trajectory generation and tracking control. A novel approach for optimizing and generating reference trajectory is proposed to construct a docking corridor that satisfies safe collision-free and visual guidance effective regions. It generates dynamically feasible and continuously smooth docking trajectories by rolling optimization. Subsequently, a docking trajectory tracking control method based on nonlinear model predictive control (NMPC) is designed, which is specifically tailored to address thruster saturation and system state constraints while ensuring the feasibility and stability of the control system. The control performance and robustness of underwater docking were validated through simulation experiments. The optimized trajectory generated is continuous, smooth, and complies with the docking constraints. The control system demonstrates superior tracking accuracy than backstepping control, even under conditions where the model has a 40% error and bounded disturbances from currents are present. The research findings presented in this study contribute significantly to enhancing safety and efficiency in deep-sea development.