期刊文献+

基于支持向量拟合代理模型的卫星多学科设计优化 被引量:1

Satellite Multidisciplinary Design Optimization Based on Support Vector Regression Surrogate Model
下载PDF
导出
摘要 为了提高卫星的设计质量与效率,建立以卫星总质量最小为优化目标的多学科设计优化问题,主要考虑轨道、有效载荷、电源和结构4个分系统的设计并梳理其耦合关系,整理并建立了较为详细且贴近工程实际的学科分析模型。本文提出了基于支持向量拟合(Support vector regression,SVR)代理模型的优化策略,并将其应用于海洋卫星多学科设计优化中。本文算例卫星参考海洋一号卫星(HY-1),优化后整星质量相对于初始质量下降了约14.1%。优化结果表明了卫星多学科优化设计(Multidisciplnary design optimization,MDO)模型的合理性和该优化策略的有效性,为进一步探索代理模型技术在卫星MDO设计当中的应用奠定了基础。 To improve the quality and efficiency in satellite design, the satellite multidisciplinary design optimization is presented with the object of minimizing total mass considering orbit, payload, power supply and structure. The paper combs the coupling tailed and practical disciplinary analysis model. The among the four subsystems and establishes the de optimization strategy is proposed based on support vector regresstion (SVR) method. The strategy is applied to multidisciplnary design optimization (MDO) of the marine satellite. The studied satellite takes Ocean 1 satellite (HY-1) as a reference, and the total mass of the satellite is reduced by 14.1 after optimization compared with the initial value. The optimization result proves the rationality of the satellite's MDO model and the effectiveness of the optimization strategy. It is of vital importance to the future work of the application of SVR metamodel in satellite MDO design.
出处 《南京航空航天大学学报》 EI CAS CSCD 北大核心 2014年第3期481-486,共6页 Journal of Nanjing University of Aeronautics & Astronautics
基金 国家自然科学基金(51105040 11372036)资助项目
关键词 海洋卫星 多学科优化设计 支持向量拟合 代理模型 marine satellite multidisciplnary design optimization support vector regression surrogatemodel
  • 相关文献

参考文献16

二级参考文献99

  • 1王书河,何麟书.飞行器多学科设计优化概述[J].宇航学报,2004,25(6):697-701. 被引量:26
  • 2裴晓强,黄海.协同优化在卫星多学科设计优化中的初步应用[J].宇航学报,2006,27(5):1054-1058. 被引量:13
  • 3汉斯 S 劳申巴赫.太阳电池阵设计手册[M].北京:宇航出版社,1987.. 被引量:1
  • 4SIMPSON T W, TOROPOV V, BALABANOV V, et al.Design and analysis of computer experiments in multidisciplinary design optimization: A review of how far we have come-or not[C]// 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, September 10-12, 2008, Victoria, British Columbia Canada. 2008: 1-21. 被引量:1
  • 5SIMPSON T W, BOOKER A J, GHOSH D, et al. Approximation methods in multidisciplinary analysis and optimization: A panel discussion[J]. Struct. Multidisc. Optim., 2004, 27: 302-313. 被引量:1
  • 6JIN R, CHEN W, SIMPSON T W. Comparative studies of metamodeling techniques under multiple modeling critieria[J]. Struct. Multidisc. Optim., 2001, 23: 1-13. 被引量:1
  • 7GUTMANN H M. A radial basis function method for global optimization[J]. Journal of Global Optimization, 2001, 19: 201-227. 被引量:1
  • 8MULLUR A A, MESSAC A, Extended radial basis functions: More flexible and effective metamodeling[J]. AIAAJournal, 2005, 43(6): 1306-1315. 被引量:1
  • 9MECKESHEIMER M, BARTON R R, SIMPSON T. Metamodeling of combined discrete/continuous responses [J]. AIAA Journal, 2001, 39(10): 1950-1959. 被引量:1
  • 10YOUNG A, CAOChengyu, PATELV, etal. Adaptive control design methodology for nonlinearin control systems in aircraft applications[J]. Journal of Guidance, Control and Dynamics, 2007, 30(6): 1770-1782. 被引量:1

共引文献104

同被引文献15

引证文献1

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部