高超风洞温度场控制精度直接影响到风洞试验数据的准确性，针对高超风洞温度场控制大延迟、非线性、多变量耦合等控制难题，对影响温度的数据进行相空间重构并将支持向量回归应用到高超风洞温度场预测控制中，提高高超风洞温度场控制的精度和效率。同时考虑到支持向量回归机中核函数的选取以及核函数参数的优化影响预测结果的精度，基于不同的核函数对支持向量机建立预测模型，对比验证分析选择最优的核函数，建立PSR-SVR模型对高超风洞温度场进行预测，提高温度预测精度，实际温度场数据分析表明了所提方法的有效性。

The precision of temperature field control in the hypersonic wind tunnel directly affects the accuracy of wind tunnel test data. In view of the control problems of hypersonic wind tunnel temperature field control, such as large delay, nonlinear and multivariable coupling, phase space reconstruction of data affecting temperature was carried out and support vector regression was applied to the hypersonic wind tunnel temperature field predictive control to improve the accuracy and efficiency of hypersonic wind tunnel temperature field control. At the same time, considering that the selection of kernel function in support vector regression machine and the optimization of kernel function parameters affect the accuracy of prediction results, the support vector machine model was established based on different kernel functions, and the optimal kernel function was selected through comparative verification and analysis, and the corresponding PSR-SVR model was established to predict the temperature field of the hypersonic wind tunnel, so as to improve the temperature prediction accuracy. The analysis of actual temperature field data shows the effectiveness of the proposed method.