关键词: 鲁棒协同优化, 鲁棒性评估, 模型不确定性, 自适应模拟退火算法

Abstract: To enhance the accuracy of robustness estimation for subsystem-level constraints in the process of robust collaborative optimization,a new method of robust collaborative optimization under mixed uncertainty was proposed.Aiming at the robust collaborative optimization problem under interval uncertainty,the formulation of subsystem-level constraints was corrected by using the method of sensitivity analysis.In the new method,not only the precision errors of input variables were included,but also the model uncertainty caused by the inconsistency of shared variables during robust collaborative optimization process was taken into consideration.The results of a numerical example showed that the accuracy of robustness estimation for subsystem-level constraints was improved significantly.The proposed method was applied to an optimization problem of satellite structure,and a desirable robust optimum solution was found by adaptive simulated annealing algorithm.Meanwhile,the applicability for the new method to robust optimization problems of complex systems was verified.

Key words: robust collaborative optimization, robustness estimation, model uncertainty, adaptive simulated annealing algorithm