Distributed Lyapunov-Based Model Predictive Formation Tracking Control for Autonomous Underwater Vehicles Subject to Disturbances

This article studies the formation tracking problem of a team of autonomous underwater vehicles (AUVs) with the ocean current disturbances. A distributed Lyapunov-based model predictive controller (DLMPC) is designed such that AUVs can keep the desired formation while tracking the reference trajectory, despite the presence of external disturbances. The DLMPC inherits the stability and robustness of the extended state observer (ESO)-based auxiliary control law and invokes online optimization to improve formation tracking performance of the multi-AUV system. The closed-loop stability of the multi-AUV system is guaranteed by the stability constraint that utilizes the ESO-based auxiliary controller and the associated Lyapunov function. Furthermore, the inter-AUV collision avoidance can be achieved by incorporating well-designed artificial potential fields-based cost term in the formation tracking cost function. Extensive simulations on the Saab Falcon AUVs are carried out, demonstrating the superior control performance and robustness of the proposed method.

Automated summary

This article studies the formation tracking problem of a team of autonomous underwater vehicles (AUVs) with ocean current disturbances, proposing a distributed Lyapunov-based model predictive controller to address this issue. It utilizes extended state observer-based auxiliary control laws and online optimization to enhance the formation tracking performance of the multi-AUV system, ensuring closed-loop stability with stability constraints and artificial potential fields for inter-AUV collision avoidance. Extensive simulations demonstrate the superior control performance and robustness of the proposed method on Saab Falcon AUVs.