基于改进的多目标进化算法的飞行控制系统优化

Optimization of aircraft flight control system based on improved multi-objective evolutionary algorithm

针对在传统飞行控制系统控制器参数整定问题中单目标优化不能同时满足多个控制指标要求的缺点,提出了一种基于改进的NSGA-II算法的多目标进化算法。在改进的NSGA-II算法中,提出了改进的精英保留策略增强算法收敛性;同时,使用改进的自适应模拟二进制(ASBX)算子提高算法效率,提出了使用改进的基于混沌序列的变异算子避免算法陷入局部最优解,以提高算法搜索精度。将改进的算法应用于飞机飞行控制系统设计中。仿真结果表明,该进化算法能够快速有效地进行飞行控制系统参数整定。

In the traditional optimization of tuning the flight control system（FCS） parameters,it is difficult to use the single object to optimal the many objects in the same time.To solve such problem,an improved NSGA-Ⅱ algorithm was proposed based on the multi-objective evolutionary optimization algorithm.In the improved NSGA-Ⅱ algorithm,presented a new elitism reserve strategy to enhance the convergence speed.Moreover,adopted a modified adaptive simulated binary crossover（ASBX） operator to increase the computational efficiency of the algorithm.And utilized the mutating operator based on the chaos sequence to avoid the chromosomes being trapped into local convergence,which could improve the precision in the searching process.Finally,applied the improved algorithm in the designing of the flight control system.The simulation result shows that the algorithm of this paper adopted can tone the parameters of the FCS rapidly.