Adaptive Fuzzy Human-in-the-Loop Control for Unmanned Surface Vehicles in Environmental Monitoring Applications

This paper presents a human-in-the-loop (HiTL) intelligent adaptive control scheme for unmanned surface vehicles (USVs) that accounts for uncertain dynamics, with the goal of effectively monitoring marine pollutants. To tackle the challenges posed by complex aquatic monitoring environments, this approach integrates human intelligence into the navigation strategy of USVs, allowing for superior path planning through human decision-making. Additionally, a potential field-based obstacle avoidance strategy is developed to ensure the safe operation of USVs within this HiTL framework. To address issues related to system uncertainties, we propose a novel adaptive fuzzy control strategy based on convex optimization, which enhances overall control performance. Finally, stability analysis and simulation results demonstrate the effectiveness of the proposed method. The verification results show that compared with traditional adaptive fuzzy controllers, our control strategy effectively reduces control errors.