不确定条件下协同设计参数鲁棒优化方法

Collaborative Parameter Robust Optimization under Uncertainty

提出了不确定条件下基于广义动态约束网络(GDCN)的协同设计参数鲁棒优化方法.分析了协同设计中的参数不确定性,基于GDCN建立协同参数鲁棒设计方法框架;在同时考虑目标属性鲁棒和约束可行域鲁棒的前提下,建立了一种带偏好信息的协同设计参数多目标鲁棒优化(MORO)模型;并给出了MORO模型的优化求解流程.通过发动机设计实例,验证了该方法的有效性和可行性.

A collaborative parameter robust optimization based on generalized dynamic constraints network （GDCN） was presented. The uncertainty of parameter in the concurrent and collaborative design was analyzed, and the GDCN was presented to manage the uncertainty. The frame of collaborative parameter robust design based on GDCN was developed. The model of multi objective robust optimization（MORO） with preference information was presented, at the same time the robustness of target attributes and dynamic constraints feasible domain were considered. And the flow of robust optimization based on MORO was given. Finally, a design example of engine was analyzed to show effectiveness of this proposed method.