Bearing-Only-Based Cooperative Target Enclosing Control for Multiple Uncrewed Surface Vehicles With Unknown Dynamics and Sideslip

Abstract

Cooperative target enclosing control for uncrewed surface vehicles (USVs) is critical in tackling complicated maritime tasks in many scenarios. This article proposes a cooperative target enclosing control framework for multi-USV systems, focusing on unknown targets under the constraints of bearing-only measurements, sideslip effects, unknown dynamics, and external disturbances. A bearing-only-based cooperative target estimator is introduced to estimate the relative position and velocity of the unknown target in practical situations where only bearing measurements are available. Cooperative states among neighboring USVs are incorporated to relax the persistent excitation (PE) condition, enhancing the estimator's robustness. A cooperative controller based on USV kinematics is designed to achieve both distance keeping and evenly spaced circumnavigation with neighbors. To account for the sideslip effects caused by the unknown sway velocity of the USVs, extended state observers are employed to estimate and compensate for the unknown kinematic terms involving sway velocity, thereby improving the target enclosing control performance. In addition, a radial basis function neural network-based dynamic controller is developed to approximate and compensate for uncertain nonlinear functions in the dynamics, ensuring the stability of individual USVs in the presence of uncertain dynamics. To address the issue of complexity explosion in online adaptive networks, a minimal learning parameters technique is adopted to reduce the number of weights that need to be online adapted to two, thereby effectively alleviating the computational load. Comparative simulations are implemented to verify the effectiveness of the proposed target enclosing framework for multi-USV systems.