基于改进粒子群算法的飞行器冲突解脱方法研究

冲突解脱要求飞行器采用一种有效的方法来满足工作环境的限制。针对飞行器在多障碍环境下的冲突解脱问题,提出一种能够满足限制条件的改进粒子群算法(PSO)对冲突进行解脱。所提出的新算法(DARPSO)相对于经典粒子群算法有2个优点:第一,考虑了障碍对寻优过程的影响;第二,具有跳出局部极小的能力。仿真实验结果显示,所提出算法的优化效果要优于标准粒子群算法。将改进后的算法应用到飞行器冲突解脱过程中并进行仿真,结果表明,所提出的算法能够有效地指导飞行器躲避障碍,完成冲突解脱。

Study of the aircraft conflict resolution method based on modified particle swarm optimization

Conflict resolution requires the aircraft to adopt an effective method to meet the constraints of the working space. Aiming at the problem of conflict resolution in multi obstacle environment, a novelty algorithm based on particle swarm optimization (PSO) is proposed for conflict resolution which meets the mentioned constrains. The proposed DARPSO is similar to PSO with two modifications: firstly, it takes into account the obstacle avoidance; secondly, it has a mechanism to escape from local optima. Various experimental results obtained in simulations show that the proposed DARPSO is much more superior than PSO. The DARPSO is applied to the process of conflict resolution of aircrafts, and it is simulated. The simulation results show that the proposed algorithm can avoid the obstacles and complete conflict resolution effectively.