| Citation: | CHENG Qiyou, LI Chunhua, JIANG Jiawei, et al. Research on MDOE methods based on response surface optimization model with adaptive genetic algorithm[J]. Journal of Aerospace Power, 2025, 40（12）：20240844 doi: 10.13224/j.cnki.jasp.20240844
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The polynomial response surface model (PRSM) was characterized by its simplicity in modeling and low computational cost, making it widely used in wind tunnel tests based on the modern design of experiments (MDOE) method. However, PRSM cannot process residuals after model fitting, leading to a loss of some model matrix information and increased parameter prediction error. To address this, a residual objective function based on the difference between predicted and measured values was constructed. Then, the crossover and mutation probabilities of the genetic algorithm (GA) were improved by calculating individual fitness values using a roulette wheel selection method. This contributed to the establishment of an MDOE method optimized by an improved adaptive genetic algorithm (IAGA) for PRSM, which was applied to aircraft wind tunnel tests. The results showed that the MDOE method required only about 35% of the experimental points needed by the one factor according to OFAT method. Compared with the traditional GA-based MDOE method, the IAGA-based MDOE method decreased the prediction error of the response surface model by 1.263% and increased the average iteration speed by 3.76 times, which effectively improved the efficiency of wind tunnel tests.
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