摘要
针对标准粒子群优化算法过早地陷入局部最优问题,提出了一种改进的粒子群优化算法,引入基于均匀设计区域选取的变异算子和改进的自适应权重来提高种群多样性和粒子群搜索效率,并应用于某飞行控制系统的优化调参。通过该方法,不但可以降低结果过早陷入局部最优的可能性,而且还提高了飞行控制系统优化调参的效果,仿真实验验证了该设计方法的有效性。
To solve the problem that the standard PSO may fall in a local optimum,an improved PSO method is proposed that selects parameters by uniform design,uses mutation operators to improve species diversity,and adaptive weights to increase the efficiency of particle swarm search.The improved particle swarm is used to optimize every parameter of flight controller.Through the method,it not only can reduce the possibility of the results into a local optimum,but also can improve the efficiency.Simulation results validate the effectiveness of the method and its efficiency.
出处
《飞行力学》
CSCD
北大核心
2011年第2期89-92,96,共5页
Flight Dynamics
关键词
飞行控制系统
粒子群优化算法
局部最优
flight control system
particle swarm optimization algorithm
local optimum
