基于约束EGO的对地观测卫星多学科设计优化

In the conceptual design phase of earth observation satellite, a mathematical model aimed at realizing optimal aggregative indicators of satellite coverage breadth and ground resolution is built to improve satellite's performance and design efficiency for optimization. A detailed multidisciplinary design optimization(MDO) analysis model is set up by considering the design variable and constraints of five sub-systems: orbit, control, payload, power and structure. Meanwhile, the existing coupling relationship is teased out and the fixed-point iteration method is employed for multidisciplinary analysis(MDA). In order to solve optimization problem with constraints, a constrained efficient global optimization method integrated with an adaptive penalty function is proposed. The optimization strategy is validated by using two benchmark engineering optimization test problems. Compared with genetic algorithm(GA) and constraint importance mode pursuing sampling(CiMPS) metamodel method, constraint efficient global optimization(C-EGO) can efficiently obtain the optimal design scheme to satisfy complex constraints. At last, the optimization problem of earth observation satellite is optimized by C-EGO, and compared with GA and CiMPS, C-EGO exhibits obvious efficiency merit. The results show that C-EGO can efficiently solve earth observation satellite MDO problem. The proposed satellite MDO models and efficient C-EGO method provide valuable references for satellite MDO study.