Collaborative Target Allocation of UAV Cluster Based on A-HPSO Algorithm
Firstly,a mathematical model was established for the problem of target allocation in close range aerial combat collaborative tasks of unmanned aerial vehicle swarms under transparent conditions.Aiming at the problem of"algorithm premature convergence"that often occurs during the problem solving process after modeling,a self de-structing hybrid particle swarm algorithm(A-HPSO)is proposed based on the hybrid particle swarm algorithm(HP-SO),which introduces a blockage detection mechanism and a forced fragmentation operation.In order to verify the re-search idea of this paper and the performance of the improved algorithm,HPSO,M-HPSO,I-HPSO and A-HPSO al-gorithms are respectively applied to the simulation experiments of six standard test target optimization functions and the simulation experiments of modeling problems under two kinds of fixed-random air combat situations.The experi-mental results show that compared with the original algorithm,the improved algorithm A-HPSO significantly overcomes the"premature algorithm"problem and further improves the convergence speed and accuracy of the HPSO algorithm in the optimization of multi-constraint and multi-objective functions.
PSOHPSOA-HPSOCooperative task assignment of UAV cluster
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