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

被引：1

作者：

Feng Z. ^{[1
]}

Wang J. ^{[1
]}

机构：

[1] School of Economics and Management, Nanjing University of Science and Technology, Nanjing

来源：

Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2019年 / 41卷 / 09期

关键词：

Multi-response; Multi-task Gaussian processes; Quality loss function; Response uncertainty; Robust parameter design;

D O I：

10.3969/j.issn.1001-506X.2019.09.18

中图分类号：

学科分类号：

摘要：

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. © 2019, Editorial Office of Systems Engineering and Electronics. All right reserved.

引用

页码：2048 / 2057

页数：9

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