Real-time guidance and control for multi-fixed-wing unmanned aerial vehicles for standoff surveillance in cluttered environment

The standoff surveillance operations (SSO) in a cluttered environment using multiple distributed fixed-wing unmanned aerial vehicle (FW-UAV)-based system present critical challenges. It requires real-time guidance for surveillance, obstacle avoidance in the flying path, and flock control. This study proposes a blended guidance and flock control (BGFC) mechanism that unifies the vector field-based hybrid guidance (VFHG) model and adaptive flock control (AFC) to address the SSO problem. Initially, the proposed VFHG model ensures that FW-UAVs follow the surveillance path while maintaining a safe distance from obstacles on the flying path within a finite time (FT). Later, the proposed AFC strategy ensures distributed flocking behavior in the multi-FW-UAV system during SSO. The dynamic nature of the FW-UAVs flock and adaptive interactions among system agents while maintaining safe clearance from each other are key features of the proposed AFC. Lyapunov stability theory is used to prove the convergence of the FW-UAV flight paths. In addition, an optimization problem is formulated to tune the design parameters of the proposed BGFC mechanism to achieve an optimal operational performance and minimize the energy consumption during the SSO. Comparative numerical simulations and real-time hardware-in-loop (HIL) tests confirm the efficiency of the proposed BGFC framework.