Collision Avoidance and Formation Tracking Control for Heterogeneous UAV/USV Systems with Input Quantization

Abstract

This study addresses the heterogeneous formation control problem for cooperative unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) operating under input quantization constraints. A unified mathematical framework is developed to harmonize the distinct dynamic models of UAVs and USVs in the horizontal plane. The proposed control architecture adopts a hierarchical design, decomposing the system into kinematic and dynamic subsystems. At the kinematic level, an artificial potential field method is implemented to ensure collision avoidance between vehicles and obstacles. The dynamic subsystem incorporates neural network-based estimation to compensate for system uncertainties and unknown parameters. To address communication constraints, a linear quantization model is introduced for control input processing. Additionally, adaptive control laws are formulated in the vertical plane to achieve precise altitude tracking. The overall system stability is rigorously analyzed using input-to-state stability theory. Finally, numerical simulations demonstrate the effectiveness of the proposed control strategy in achieving coordinated formation control.

Keywords

• UAVs
• USVs
• input quantization
• hierarchical design
• an artificial potential field