TY - GEN
T1 - Metamodel Assisted Multidisciplinary Design Optimization for Satellite with a Large-Size Payload
AU - Tai, Xinhui
AU - Shi, Renhe
AU - Chen, Yujun
AU - Long, Teng
AU - Ye, Nianhui
N1 - Publisher Copyright:
© 2023, Beijing HIWING Sci. and Tech. Info Inst.
PY - 2023
Y1 - 2023
N2 - To settle the challenge of complex satellite system design, the multidisciplinary design optimization (MDO) problem for a satellite with a large-size payload is investigated in this paper. The satellite MDO problem is defined to minimize the overall mass subject to several practical constraints such as the structural natural frequency and transfer time. Then, considerable efforts are made to establish the analysis models of orbital transfer, space environment, power, geometry, structure, and mass disciplines, considering the inter-coupled relationship between the satellite platform and the payload. Furthermore, a filter-based sequential radial basis function (FSRBF) method is employed to settle the studied satellite MDO problem efficiently and effectively. In this approach, a radial basis function is constructed and adaptively refined to approximate the expensive multidisciplinary analysis (MDA) models for optimization, which notably lowers the computational cost. After optimization, the overall mass of the satellite is successfully reduced by 116.17kg (3.35%) compared with that of the initial design, and all the constraints are met. Moreover, the cost of the metamodel-based optimization method is only 24.1% of that of the differential evolutionary algorithm, which indicates the practicality and effectiveness of this study.
AB - To settle the challenge of complex satellite system design, the multidisciplinary design optimization (MDO) problem for a satellite with a large-size payload is investigated in this paper. The satellite MDO problem is defined to minimize the overall mass subject to several practical constraints such as the structural natural frequency and transfer time. Then, considerable efforts are made to establish the analysis models of orbital transfer, space environment, power, geometry, structure, and mass disciplines, considering the inter-coupled relationship between the satellite platform and the payload. Furthermore, a filter-based sequential radial basis function (FSRBF) method is employed to settle the studied satellite MDO problem efficiently and effectively. In this approach, a radial basis function is constructed and adaptively refined to approximate the expensive multidisciplinary analysis (MDA) models for optimization, which notably lowers the computational cost. After optimization, the overall mass of the satellite is successfully reduced by 116.17kg (3.35%) compared with that of the initial design, and all the constraints are met. Moreover, the cost of the metamodel-based optimization method is only 24.1% of that of the differential evolutionary algorithm, which indicates the practicality and effectiveness of this study.
KW - Large-size payload
KW - Metamodel-based optimization
KW - Multidisciplinary analysis model
KW - Multidisciplinary design optimization
KW - Satellite conceptual design
UR - http://www.scopus.com/inward/record.url?scp=85151051239&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-0479-2_241
DO - 10.1007/978-981-99-0479-2_241
M3 - Conference contribution
AN - SCOPUS:85151051239
SN - 9789819904785
T3 - Lecture Notes in Electrical Engineering
SP - 2611
EP - 2624
BT - Proceedings of 2022 International Conference on Autonomous Unmanned Systems, ICAUS 2022
A2 - Fu, Wenxing
A2 - Gu, Mancang
A2 - Niu, Yifeng
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Autonomous Unmanned Systems, ICAUS 2022
Y2 - 23 September 2022 through 25 September 2022
ER -