飞机飞行控制系统参数多目标优化设计研究

针对传统飞行控制律参数单目标优化设计不能同时满足多控制指标要求,且与飞行品质要求缺乏相关性,物理意义不明确等缺点,提出了一种基于改进粒子群算法的飞行控制律多目标优化设计方法。算法模拟鸟类捕食过程,使得种群随着"食物"的发现和消耗,聚集为数量和构成动态调整多个子群,且子群粒子速度也随之进行自适应变异,从而有利于维持种群的多样性,有效抑制早熟收敛现象发生。最后,使用改进的粒子群优化算法对某型飞机纵向控制律设计进行数值仿真,结果显示,算法有效提高控制律优化调参效率,结果满足期望的飞行品质要求。

Research on Multi-objective Optimal Parameters Design of Aircraft Flight Control System

In the traditional optimization design of flight control system （FCS）,there are some disadvanta-ges such as weak correlation between the single object and the flight quality requirements , ambiguous physical meaning and difficulty of using single object to optimize many objects at the same time .To solve such problem ,an improved particle swarm optimization （ PSO） algorithm was proposed .By simulating the foraging aggregation behavior of birds ,the particles can be divided into several dynamic sub-swarms with respect to the finding and expanding of forage in the improved PSO algorithm .So that ,the diversity of par-ticles can be maintained by this method , thus can restrain local optimum phenomena .Finally , using the improved PSO algorithm for numerical simulation of a certain type of aircraft longitudinal control law ,the results show that the proposed algorithm can effectively improve the efficiency of the FCS parameters tun-ing,and the results can meet the flight qualities requirements .