基于IPSO的舰载机出动离场规划研究

Research on departure planning of carrier aircraft based on IPSO

针对舰载机机群出动离场效率问题,提出了一种改进的粒子群优化(improved particle swarm optimization, IPSO)算法。首先,基于舰载机的出动离场流程及约束建立了舰载机出动离场数学模型,并根据出动离场问题特点设计了一种连续编码形式以表示出动规划方案。然后,通过在参数自适应粒子群优化算法的基础上引入基于莱维飞行扰动的模拟退火机制,提出了将IPSO用于对出动离场规划问题进行求解。最后,分别针对8、10、12机的出动离场规划场景进行了仿真验证。仿真结果表明,所提算法较已有的优化算法而言具有更好的寻优能力。

An improved particle swarm optimization(IPSO)algorithm is proposed to address the problem of departure efficiency for carrier aircraft.Firstly,a mathematical model for the departure process and constraints of carrier aircraft is established,and a continuous coding form is designed to represent the departure planning scheme based on the characteristics of the departure problem.Then,by introducing a simulated annealing mechanism based on Levy flight disturbance on the basis of parameter adaptive particle swarm optimization algorithm,the IPSO algorithm is proposed for solving the departure planning problem.Finally,simulation verification is conducted for the departure planning scenarios of aircraft 8,10,and 12 respectively.The simulation results indicate that the proposed algorithm has better optimization ability compared to existing optimization algorithms.