高效粒子群算法研究及飞翼无人机气动隐身优化设计  

Research on Efficient Particle Swarm Optimization and Aerodynamic Stealth Integrated Design of Fly-wing UAV

作　　者：樊华羽 詹浩[1] 程诗信 米百刚 姚会勤 Fan Huayu;Zhan Hao;Cheng Shixin;Mi Baigang;Yao Huiqin(School of Aeronautics,Northwestern Polytechnical University,Xi’an 710072,China;School of Aerospace Engineering,Tsinghua University,Beijing 100084,China)

机构地区：[1]西北工业大学航空学院,西安710072 [2]清华大学航天航空学院,北京100084

出　　处：《航空工程进展》2019年第6期735-743,共9页Advances in Aeronautical Science and Engineering

摘　　要：飞行器气动隐身多目标优化设计存在计算代价过大的问题,亟需一种高效的优化设计方法来解决此类问题。以某型无人机为设计对象,采用自由曲面变形(FFD)方法实现飞翼布局的参数化表达,分别采用基于雷诺平均N灢S方程的计算流体力学方法、大面元物理光学法和一致性几何绕射理论相互配合来计算边缘绕射场的RCS,进而计算飞翼布局无人机的气动、隐身性能;选择结合基于动态超体积期望改善(EHVI)加点的动态Kriging代理模型与ASMOPSO算法的高效多目标粒子群算法对飞翼布局无人机进行综合寻优设计。在较少地调用真实目标函数的情况下,获得了比较优秀的Pareto前沿,表明优化后的飞翼布局无人机在气动及隐身方面均优于原始构型。To deal with the problem of aerodynamic and stealth integrated optimization of fly-wing UAV,a multi-objective optimization study on aerodynamic and stealth of the fly-wing UAV is carried out which based on the free-form surface deformation(FFD).The FFD parametric method is used to parameterize the wing surface;CFD calculation based on N-S equations is used to analyze the aerodynamic performance of the fly-wing UAV,large element physical optical method and uniform theory of diffraction are used to calculate radar cross-section(RCS)of the fly-wing UAV.And ASMOPSO algorithm with the Kriging surrogate model which based on the expect hyper-volume improvement(EHVI)infill criterion is adopted for integrated optimization design.The results of fly-wing UAV aerodynamic and stealth integrated optimization exhibit considerable improvement.

关 键 词：飞翼布局无人机 EHVI加点 ASMOPSO优化算法 气动隐身多目标优化 

分 类 号：V211.41[航空宇航科学与技术—航空宇航推进理论与工程]