Hybrid swarm intelligent algorithm for multi-UAV formation reconfiguration

Abstract Formation flight of unmanned aerial vehicles (UAVs) utilizes reconfiguration procedures to handle a variety emergencies, such as collision avoidance, malfunctions, fuel savings, and member replacement. As UAVs have limited computing power energy resources, it is necessary optimize the control inputs reduce distance travelled by while reducing costs during formation reconfiguration. In this paper, problem multi-UAV decoupled into two stages: task assignment input optimization UAVs. For solution above problem, we propose an adaptive hybrid particle swarm differential evolution algorithm (AHPSODE) minimize total movement cost Based on idea receding horizon (RHC) nonlinear model reconfiguration, RHC controller using AHPSODE designed UAV group obtain shortest distance, method can computation time. We use CEC 2017 test suit performance our proposed algorithm, simulate AHPSODE-based manage The results show that performed well in convergence accuracy effective.