To meet the requirements of formation control and maneuverability in multiple unmanned surface vehicle (USV) systems operating in irregular environments, a distributed cooperative maneuvering target tracking control method based on affine transformation is proposed.

First, a novel output redefinition-based dynamic transformation method is proposed to address the absence of relative degree in underactuated USV systems, thereby simplifying the control design process. Subsequently, a distributed target velocity observer is designed to estimate the unknown velocity of moving targets. Based on the estimated target velocity, a distributed target tracking control strategy is developed by integrating affine transformation theory with backstepping control to enable agile tracking of moving targets. To address unknown model parameters and external disturbances, an adaptive law is constructed using the minimum learning parameter (MLP) technique and radial basis function neural network (RBFNN) for online estimation.

Simulation results demonstrate that the proposed control method enables effective tracking of moving targets in irregular environments. When targets navigate through narrow passages, the multi-USV system flexibly adjusts its formation to avoid obstacles, exhibiting both robustness and flexibility.

The proposed affine transformation-based control method enhances both the flexibility and safety of multi-USV systems in tracking moving targets in irregular environments. This work provides a significant advancement in distributed cooperative control strategies for multi-USV systems and offers practical value for maritime surveillance and rescue operations.