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。 Aiming at the premature convergence of the standard particle swarm optimization algorithm into the local optimization problem, an improved particle swarm optimization algorithm is proposed. The mutation operator based on uniform design region selection and improved adaptive weight are introduced to improve the population diversity and particle swarm optimization Search efficiency, and applied to a flight control system optimization parameters. The method not only can reduce the possibility of the result getting into the local optimum prematurely, but also improves the effect of the optimization of the flight control system. Simulation results show the effectiveness of the design method.