基于仿真模型的鲁棒协同优化方法研究

复杂产品往往由多个子系统通过复杂的耦合方式组成.针对复杂产品的多学科鲁棒设计优化技术已得到广泛应用.为了使用仿真模型进行多学科鲁棒设计优化,提出了SUA-RCO和DRS-RCO两种方法.在SUA-RCO方法中,仿真模型首先被拟合为近似的数学模型,然后利用近似数学模型进行RCO计算.系统的不确定性由SUA方法进行计算.为了解决大参数方差问题,DRS-RCO方法将仿真模型近似拟合为双响应面形式,分别使用两个响应面来拟合均值和方差.然后,进行协同优化计算.

Study of Robust Collaborative Optimization Based on Simulation Models

Robust multidisciplinary design optimization has been widely used in the design of complex products which have many subsystems through complex couplings. In order to do robust collaborative optimization based on simulation models, two methods were developed. In SUA-RCO framework, the simulation models were fitted to approximate models, and the RCO was calculated with the mathematic expression of the approximate models. The uncertainty was included in system uncertainty analysis method. In order to solve the large parameter variation problems, the DRS-RCO method put the simulation models to dual response surfaces which put the uncertainty into the dual-response surface of mean and variation.