CAJ | 학술논문

针对多无人作战飞机(unmanned combat aerial vehicle, UCAV)协同目标分配问题,提出了一种基于离散粒子群算法的多UCAV协同目标分配方法.根据多UCAV协同目标分配问题的特点,建立了粒子与实际问题间的映射,设计了新的粒子群位置和速度更新公式,并且对标准粒子群算法作了改进.充分利用粒子群优化算法的全局搜索能力,有效地解决多约束条件下多UCAV协同目标分配问题.仿真结果表明,离散粒子群算法能够稳定快速地找到较优分配方案,并且算法简单、灵活.
침대다무인작전비궤(unmanned combat aerial vehicle, UCAV)협동목표분배문제,제출료일충기우리산입자군산법적다UCAV협동목표분배방법.근거다UCAV협동목표분배문제적특점,건립료입자여실제문제간적영사,설계료신적입자군위치화속도경신공식,병차대표준입자군산법작료개진.충분이용입자군우화산법적전국수색능력,유효지해결다약속조건하다UCAV협동목표분배문제.방진결과표명,리산입자군산법능구은정쾌속지조도교우분배방안,병차산법간단、령활.
A discrete particle swarm optimization (DPSO) algorithm is put forward for multi-UCAV (unmanned combat aerial vehicle)cooperation mission assignment problems. In the algorithm, a new code for particles and new update strategy for the position and speed of particles are applied so as to make the DPSO algorithm more suitable for multi-UCAV cooperation mission assignment problems. Aiming at the shortcoming of prematurity and poorness resulted from pure PSO, the DPSO algorithm takes full advantage of the complementary strengths of the particle swarm optimization algorithm, and the algorithm could solve multi-UCAV cooperation mission assignment effectively. The simulation results show that the DPSO algorithm could find the better assignment scheme fleetly and is simple and flexible.