基于改进粒子群算法的高速载荷控制参数优化

High-speed load control parameter optimization based on improved particle swarm algorithm

高速载荷入水前需要实现合成攻角的瞬时控制,而高速载荷瞬时姿态控制参数是决定高速载荷能否在合理的合成攻角范围内入水的关键。因此,针对高速载荷瞬时姿态控制参数的整定与优化,本文设计一种改进的粒子群优化算法,设计惯性权重自适应调整方式,使不同粒子根据自身搜索效果产生不同的惯性权重,并且引入遗传算法的思想改善粒子群的搜索能力,从而提高粒子群优化算法的寻优能力,得到恶劣初始条件下高速载荷瞬时姿态控制较高的寻优成功率。

The instantaneous control of the synthetic angle of attack needs to be realized before the high-speed load enters the water,and the instantaneous attitude control parameter of the high-speed load is the key to determining whether the high-speed load can enter the water within a reasonable synthetic angle of attack.Therefore,aiming at the tuning and optimization of instantaneous attitude control parameters of high-speed loads,an improved particle swarm optimization algorithm is designed,which designs the adaptive adjustment method of inertial weights,so that different particles produce different inertia weights according to their own search effects,and the idea of genetic algorithm is introduced to expand the search range of particle swarms,so as to improve the optimization ability of particle swarm optimization algorithms,and obtain a high optimization success rate of instantaneous attitude control of high-speed loads under harsh initial conditions.