摘要
针对航空专业仿真训练中的飞行器轨迹优化求解精度不高的问题,提出一个基于轨迹优化算法的航空虚拟仿真教育管理平台。首先,对飞行器轨迹优化目标函数和约束条件进行确定,然后采用改进的GA算法对飞行器轨迹进行优化求解;最后搭建一个基于轨迹优化算法的虚拟仿真教育管理平台。实验结果表明,提出的GA算法的收敛速度为11.55 ms,寻优精度为97.34%,明显优于传统的PSO算法和AGO算法,且该算法的最终收敛结果与优化结果误差均控制在合理范围内,轨迹优化求解时长较短,可提升飞行器飞行效率。仿真测试可知,基于本算法进行飞行器轨迹优化求解后,将其应用到飞行器仿真模型中可实现飞行器飞行过程的三维可视化,从而提高航空专业仿真训练和教学效果,具备有效性。
To address the issue of low accuracy in trajectory optimization for aircraft in aviation simulation training,a virtual simulation education management platform based on trajectory optimization algorithms is proposed.First,the objective function and constraints for aircraft trajectory optimization are determined.Then,an improved GA algorithm is used to optimize the aircraft trajectory.Finally,a virtual simulation education management platform based on trajectory optimization algorithms is established.Experimental results show that the proposed GA algorithm has a convergence speed of 11.55 ms and an optimization accuracy of 97.34%,significantly outperforming traditional PSO and AGO algorithms.The final convergence results and optimization results are both within reasonable error ranges,with a shorter trajectory optimization solution time,which can improve aircraft flight efficiency.Simulation tests indicate that after applying the aircraft trajectory optimization solution based on this algorithm to the aircraft simulation model,it enables three-dimensional visualization of the aircraft’s flight process,thereby enhancing the effectiveness of aviation professional simulation training and teaching.
作者
杨甜
秦伟艳
YANG Tian;QIN Weiyan(Xi’an Aeronautical Polytechnic Institute,Xi’an 710089,China)
出处
《自动化与仪器仪表》
2025年第7期229-233,共5页
Automation & Instrumentation
基金
陕西省教育教学改革课题《市域产教联合体背景下“五金”改革的研究与实践》(23GW005)
陕西省中华职教课题《产教融合背景下“金课”建设研究与实践》(ZJS202485)。
关键词
飞行器
轨迹优化求解
遗传算法
虚拟仿真
航空专业
aircraft
trajectory optimization solution
genetic algorithm
virtual simulation
aviation major
作者简介
杨甜(1994-),女,陕西西安人,硕士,讲师,主要研究方向为物流工程。
