考虑响应共变特性的多响应稳健参数设计

针对响应共变特性的稳健参数设计问题,在多任务高斯过程(multi-task Gaussian processes,MTGP)建模框架下,结合质量损失函数和考虑响应不确定性的优化函数构建了一个考虑输出响应不确定性的MTGP(uncertainty of MTGP,UNMTGP)优化模型。首先,利用MTGP模型拟合实验数据,构建考虑响应间共变特性对优化结果影响的多元高斯模型。其次,提出考虑输出响应不确定性的优化目标函数,构建多响应稳健优化模型。最后,结合全局优化方法,获得最优参数设计。此外,结合真实案例,利用质量损失函数的相关评价指标,论证所提方法的有效性。结果表明,所提方法考虑了响应共变特性和输出响应不确定性对优化结果的影响,有效改善了模型的预测质量,提升了输出响应的稳健性。

Multi-response robust parameter design based on covariant characteristics of model responses

Considering the robust parameter design of multi-response robust parameters in response to the common variation characteristics, an optimization model is constructed in the framework of multi-task Gaussian processes (MTGP) modeling, combining the mass loss function and the response uncertainty optimization function considering the uncertainty of MTGP (UNMTGP). Firstly, a multivariate Gaussian model considering the response to optimization results is constructed based on the fitting test data of the MTGP model. Secondly, the objective function of uncertain optimization considering the output response is proposed to build a multi-response robust optimization model. Finally, the optimal parameter design is obtained by combining the global optimization method.In addition, combining real cases and using the relevant evaluation indexes of the mass loss function, the validity of the method proposed in this paper is demonstrated. The results show that the proposed method can effectively improve the predictive quality of the model and improve the robustness of the output response by taking into account the influence of response covariation and output uncertainty on the optimization results.