DDPG方法在抖振约束下变弯度翼型/机翼设计的应用研究  

Application Study on the DDPG Method for Designing Variable Camber Airfoils/Wings Under Buffeting Constraints

作　　者：周思历 孙刚 王聪 ZHOU Sili;SUN Gang;WANG Cong(Department of Aeronautics&Astronautics,Fudan University,Shanghai 200433,P.R.China)

机构地区：[1]复旦大学航空航天系,上海200433

出　　处：《应用数学和力学》2024年第1期45-60,共16页Applied Mathematics and Mechanics

摘　　要：变弯度技术可以提升巡航多升力系数工况下的升阻性能,对于提高整段巡航的经济效益具有重要意义.构造了光滑连续的流动分离函数约束翼型抖振性能,结合变弯度技术与人工神经网络代理模型搭建了某机翼截面翼型的巡航多升力系数工况优化模型.应用深度确定性策略梯度(DDPG)方法优化此模型,实现了抖振约束下6.8%的巡航平均升阻比提升,优于粒子群和改进灰狼算法对此模型的优化结果.以优化前后翼型分别生成锥形后掠翼,验证了二维翼型变弯度优化对三维机翼的贡献.The application of the variable camber technology has promising results in improving the lift-to-drag performance during the cruise phase,particularly under multi-lift conditions.This improvement is crucial for enhancing the economic benefits of the entire flight.A smooth and continuous flow separation function was de-veloped to constrain the buffeting performance.An optimization model for cruise performances under multi-lift conditions of wing cross sections was constructed through combination of this function with the variable cam-ber technology and an artificial neural network surrogate model.The deep deterministic policy gradient(DDPG)method was used to optimize this model,resulting in a cruise average lift-to-drag ratio improvement of 6.8%under buffeting constraints.This improvement surpasses the results obtained by other optimization al-gorithms,such as the particle swarm optimization(PSO)and the improved gray wolf optimization(GWO).The results of the generation and analysis of 2 conical swept wings with the unoptimized and optimized airfoils,show the contribution of the 2D variable camber airfoil optimization to 3D wings.

关 键 词：气动外形优化 DDPG 变弯度 抖振 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] V221.3[自动化与计算机技术—控制科学与工程]