关键词: 多飞行器协同, 任务分配, 粒子群优化算法, 局部收敛, 模拟退火原理

Abstract:

An improved particle swarm optimization (PSO) algorithm for multi-aircraft cooperative task assignment is proposed. The corresponding mathematical model is developed by considering the constraints of the aircraft’s capability, the threat cost, the range cost, and the benefits obtained by completing the tasks. The position attribute of particles is encoded as a set of task assignment vectors, from which we can decode the task assignment solution such that the PSO solution is discretized. In order to solve the problem that the PSO algorithm can easily fall into local convergence, a strategy of jumping out of the local convergence is proposed. Based on the simulated annealing algorithm, this strategy first generates new particles, and then decides whether to retain the new particles with a certain probability. Finally, this jumping-out strategy is applied to the conventional PSO algorithm so as to establish an improved one that can be used for multi-aircraft cooperative task assignment. The digital simulation results verify the effectiveness of the proposed algorithm.

Key words: multi-aircraft cooperation, task assignment, particle swarm optimization algorithm, local convergence, simulated annealing