基于粒子群算法的长航时无人机翼型快速优化设计  

Efficient Optimization of Long-endurance UAV Wing Based on PSO Algorithm

作　　者：安林雪[1] 龙腾[1] 黄波[1] 齐竹昌[1] 彭磊[1] 刘莉[1] 

机构地区：[1]北京理工大学宇航学院,北京100081

出　　处：《弹箭与制导学报》2013年第3期119-122,共4页Journal of Projectiles,Rockets,Missiles and Guidance

基　　金：国家自然科学基金(51105040);航空科学基金(2011ZA72003);北京理工大学优秀青年教师资助计划(2011CX0402)资助

摘　　要：针对长航时无人机翼型气动性能优化的需求,将CFD分析技术、PSO算法与RBF代理模型方法相结合,提出了一种长航时无人机翼型快速优化设计方法。采用正交基函数描述翼型外形,并通过求解N-S方程获得翼型气动性能。使用标准粒子群优化算法对翼型气动性能进行优化,以提高全局收敛性。考虑到CFD气动分析存在计算耗时的缺点,通过径向基函数代理模型对CFD气动分析模型进行近似,以达到提高优化效率的目的。长航时无人机翼型优化算例研究表明,所提出的快速优化方法在保证优化设计质量的前提下,可以有效地降低优化计算成本,提高优化效率,具有较高的工程实用性。For the purpose of optimization on airfoil＇s aerodynamic performance inlong-endurance UAV（LEUAV）,an efficient optimization design approach for the airfoil was proposed,which combined CFD analysis technique with particle swam optimization（PSO） algorithm with radial basis function（RBF） surrogate model method.The airfoil geometry was formulated by orthogonal basis functions method,then by solving N-S formulation,the aerodynamic performance was obtained.The standard PSO algorithm was employed in the optimization in order to improve the global convergence.Due to the higher computational cost,RBF surrogate model was used to approximate to CFD aerodynamic analysis model to improve optimization efficiency.The results of case studies demonstrate that under the premise of guaranteeing optimization design quality,this approach has reduced computation burden and shortened the design circle,which is also proved to be practicable in engineering.

关 键 词：翼型优化设计 粒子群优化算法 代理模型 长航时无人机 

分 类 号：V279[航空宇航科学与技术—飞行器设计]