Strong Prescribed-Time Multiple Targets Hunting Control for Marine Vehicles: A Hybrid Mapping Approach

作者：Shengjia Chu, Ning Li · 发表于：IEEE Transactions on Intelligent Transportation Systems · 年份：2025 · DOI：10.1109/tits.2025.3564941 · 被引用次数：2 · 研究领域：Maritime Navigation and Safety、Advanced Control Systems Optimization、Advanced Algorithms and Applications

This paper proposes a strong prescribed-time multiple targets hunting control scheme for marine vehicles, including the cooperative hunting guidance strategy and the prescribed-time control algorithm. A real-time task allocation mechanism is introduced to dynamically assign hunting vehicles to multiple targets. By integrating both current and predicted target states, a dynamic attractive potential field is established to guide hunting vehicles toward favorable hunting positions. To ensure navigation safety, a repulsive potential field is designed in compliance with the International Regulations for Preventing Collisions at Sea (COLREGs). An obstacle speed-regulated mechanism is proposed to dynamically adjust the repulsive influence region. Moreover, a global prescribed-time control algorithm is proposed based on the hybrid mapping scheme to achieve strong convergence. A finite and continuous gain function prevents the typical singularity problem. Furthermore, a prescribed-time disturbance observer is constructed to compensate for model uncertainties and disturbances, improving system robustness in dynamic ocean environments. Through Lyapunov theory, all signals of the closed-loop system are guaranteed to be globally uniformly bounded at the prescribed time. The experiment results demonstrate the effectiveness of the proposed target hunting control scheme.