The Multi-Disciplinary Optimization for Aircraft Design Based on Self-Adaptive Approximation Model

摘要

Aircraft design is a complicated multistage process, involving many disciplines such as aerodynamics, structure, propulsion and so on. These disciplines are intrinsically coupled to one another. Multidisciplinary Design Optimization (MDO) is a kind of optimization strategy for coupled systems. The MDO philosophy pertains to decomposition of a large complex system into several smaller, more manageable subsystems, with the inherent coupling managed by coupling terms and appropriate approximation algorithms. In this paper, the traditional concurrent subspace optimization based on response surface method (RSCSSO) was studied. Then the RSCSSO based on self-adaptive approximation model were developed. In order to reduce the amount of disciplinary analysis and keep the accuracy of the approximation models, uniform experiment design was introduced to replace the disciplinary optimization to obtain a set of design points directly. Since the quality of system level optimum and the speed of convergence largely depended on the accuracy of the approximation model, self-adaptive approximation algorithm was introduced in system level optimization. The accuracies of two approximation models were compared in each iteration and the better model would be used.The proposed RSCSSO algorithm is validated by a hand-launch UAV test case.In comparison with the traditional RSCSSO optimization and the improved RSCSSO developed by us, it can be seen that better optimum is found by improved RSCSSO with much less calculation cost.