Adaptive USV trajectory tracking: Preview-optimized rudder controller with self-tuning dynamics model

This paper addresses the critical challenge of trajectory tracking control for unmanned surface vehicles, focusing on two practical obstacles: performance degradation under rudder rate constraints and the difficulty in adapting dynamic models across varying operational conditions and vessel parameters. To overcome these issues, we propose an adaptive control framework integrating a preview-optimized rudder controller with a self-tuning dynamics model. The proposed approach employs a preview mechanism that anticipates future trajectory changes and proactively optimizes rudder commands within rate limits, substantially mitigating overshoot and maintaining high tracking accuracy. This controller is enhanced by an adaptive dynamics model that automatically calibrates itself using limited real-world data, ensuring reliable prediction performance and facilitating seamless transfer from simulation to real-world applications. Extensive simulations and sea trials under various challenging scenarios, including high-inertia loads and complex paths, consistently demonstrate the proposed method’s effectiveness in resolving the dual challenges of rate-limited actuation and model generalization, ultimately achieving superior tracking accuracy and robust performance.