基于移动最小二乘法的气动力数据建模方法

针对一体化飞行器高度耦合的非线性气动问题,提出了一种基于移动最小二乘法的气动力数据建模方法;首先,对影响模型精度的因素进行了分析;接着,在构建移动最小二乘模型时采用遗传算法获取最佳支撑域半径以及最佳影响因子β,提高近似精度从而达到减少样本点的目的;得到泛化能力较强的气动力模型,并与偏最小二乘方法的建模结果进行对比;实验结果表明:移动最小二乘法的建模效果优于偏最小二乘方法,预测误差较小,证明了将该方法应用于气动数据建模是可行的。

Aerodynamic data modeling method based on moving least square method

An aerodynamic data modeling method based on moving least square method is proposed to solve the nonlinear aerodynamic problem of highly coupled integrated aircraft. Firstly, the factors affecting the accuracy of the model are analyzed. Then, the genetic algorithm is used to obtain the optimal radius of support domain and the optimal influence factor to improve the approximate accuracy and reduce the sample points. The aerodynamic model with strong generalization ability is obtained and compared with the partial least squares method. The experimental results show that the modeling effect of the moving least squares method is better than that of the partial least squares method, and the prediction error is smaller, which proves that it is feasible to apply this method to aerodynamic data modeling.