Robust parameter design for nonlinear signal–response systems using kriging models

ABSTRACT

Most of the literature on robust parameter design concerns simple response systems; however, many engineering systems can be described as signal–response systems, in which the relationship between the signal factor and response is linear or nonlinear. In this article, a robust parameter design method is proposed to optimize nonlinear signal–response systems. To make the signal–response relationship insensitive to noise factors, the variation model and response model are developed using kriging models. In the variation model, the mean and standard deviation of the variation in response over the range of the signal factor are fitted and then synthesized as the robustness criterion, which is minimized to optimize the settings of control factors. The response model is used to obtain the fitting model of the signal–response relationship at the optimal setting of control factors. The applicability and efficiency of the proposed method are demonstrated using an engineering case.

KEYWORDS:

• Robust parameter design
• signal–response systems
• nonlinear relationship
• variation
• kriging model

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant numbers 51175315 and 61573233]; and the Natural Science Foundation of Guangdong Province [grant number 2015A030311017].