粒子群算法在等效系统拟配中的应用

PSO for Analog-Matching of Equivalent System

等效系统方法是评价飞机飞行品质的重要方法之一。采用粒子群算法进行等效系统拟配,针对粒子群算法在全局搜索和局部开发能力的平衡问题,引进了自适应调节参数,线性调节粒子速度中个体"经验"和群体共享"信息"的权重,使得算法在迭代前后期都有较强的寻优能力,最后将改进算法应用于某型飞机横航向操纵系统的等效系统拟配计算,采用失配包络线对拟配精度进行了检验。结果表明,粒子群算法在等效拟配计算中是有效可行的。

Equivalent system is one of the key methods for assessing the flying qualities of modern aircraft with a flight control system, and the Particle Swarm Optimization（PSO） was used to optimize the parameters of low-order equivalent system. An adaptive regulation parameter was introduced to balance the global search and local exploitation capability of PSO, which adjusted the weighting value between individual and group linearly. The proposed algorithm has better optimization performance during the whole calculation progress and was used for equivalent system analog-matching of lateral and directional control system. The analog matching precision was validated by the mismatch curve. The result shows that PSO is feasible and effective in low-order eauivalent system.