Robust Collaborative Optimization Method Based on Dual-response Surface

被引:7
作者
Wang Wei [1 ]
Fan Wenhui [1 ]
Chang Tianqing [2 ]
Yuan Yuming [1 ]
机构
[1] Tsinghua Univ, Natl CIMS Engn Res Ctr, Beijing 100084, Peoples R China
[2] Acad Armored Force Engn, Dept Control Engn, Beijing 100072, Peoples R China
基金
中国国家自然科学基金;
关键词
multidisciplinary design optimization; robust design; dual-response surface; TAGUCHI;
D O I
10.3901/CJME.2009.02.169
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
A novel method for robust collaborative design of complex products based on dual-response surface (DRS-RCO) is proposed to solve multidisciplinary design optimization (MDO) problems under uncertainty. Collaborative optimization (CO) which decomposes the whole system into a double-level nonlinear optimization problem is widely accepted as an efficient method to solve MDO problems. In order to improve the quality of complex product in design process, robust collaborative optimization (RCO) is developed to solve those problems under uncertain conditions. RCO does optimization on the linear sum of mean and standard deviation of objective function and gets an optimal solution with high robustness. Response surfaces method is an important way to do approximation in robust design. DRS-RCO is an improved RCO method in which dual-response surface replaces system uncertainty analysis module of CO. The dual-response surface is the approximate model of mean and standard deviation of objective function respectively. In DRS-RCO, All the information of subsystems is included in dual-response surfaces. As an additional item, the standard deviation of objective function is added to the subsystem optimization. This item guarantee both the mean and standard deviation of this subsystem is reaching the minima at the same time. Finally, a test problem with two coupled subsystems is conducted to verify the feasibility and effectiveness of DRS-RCO.
引用
收藏
页码:169 / 176
页数:8
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