基于混沌粒子群优化算法的弹性飞机模型降阶  

Model Reduction of Elastic Aircraft Based on Chaos-particle Swarm Optimization Algorithm

作　　者：章萌[1] 章卫国[1] 孙勇[1] 宁东方[1] 

机构地区：[1]西北工业大学自动化学院,西安710072

出　　处：《系统仿真学报》2009年第23期7413-7417,共5页Journal of System Simulation

摘　　要：传统的弹性飞机模型降阶算法主要有平衡截断法、平衡奇异摄动法等,但这些算法的缺陷就是得到的降阶模型只适用于特定的频段内。以某弹性飞机纵向运动模型为例,在合理选择时域模型降阶匹配误差函数的基础上,首次将混沌粒子群优化算法用于弹性飞机的模型降阶。仿真结果表明,与传统的弹性飞机模型降阶算法相比,基于混沌粒子群优化算法得到的降阶模型能在更宽广的频域内和时域内更好地近似全阶模型,取得了更好的降阶效果。Traditional model reduction algorithms of the elastic aircraft include balanced truncation algorithm,balanced singular perturbation algorithm and so on,but the defect of these algorithms is the reduced models based on these algorithms only suitable for specific frequency domain.Taking elastic aircraft longitudinal model as an example,the chaos-PSO algorithm was utilized firstly to the model reduction of the elastic aircraft based on the selecting of reasonable matching error function of the model reduction in time domain.Contrasted with the traditional model reduction algorithm,the simulation results show that the reduced model based on the chaos-PSO algorithm can give a more approximate result to the full-order model of elastic aircraft in more wide frequency domain and time domain,and the better model reduction results are obtained.

关 键 词：弹性飞机 模型降阶 混沌 粒子群优化 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]