Multidisciplinary Collaborative Optimization of Mars Probe Based on Dynamic Penalty Function

Journal of Deep Space Exploration ›› 2017, Vol. 4 ›› Issue (3) : 276 -280,292.

PDF (681KB)
Journal of Deep Space Exploration ›› 2017, Vol. 4 ›› Issue (3) : 276 -280,292. DOI: 10.15982/j.issn.2095-7777.2017.03.012

Multidisciplinary Collaborative Optimization of Mars Probe Based on Dynamic Penalty Function

Author information +
History +
PDF (681KB)

Abstract

Focusing on the system design problem of Mars probe which is far away from the Earth and has the complex flight environment,the optimization function with comprehensive objective combined by coverage rate and ground sample distance was set up. Considering the orbit discipline,the payload discipline and the power discipline,the system-level and discipline-level optimization model of the Mars probe were established based on the cooperative optimization method,thus decomposing the complicated optimization problem into parallel cooperative optimization problems with multiple sub-disciplines. The adaptive dynamic penalty function is used to accelerate the convergence. The numeric results indicate that the collaborative optimization can be successfully applied in the system optimal design of Mars probe.

Keywords

Mars probe / system optimal design / modeling / collaborative optimization / penalty function

Cite this article

Download citation ▾
null. Multidisciplinary Collaborative Optimization of Mars Probe Based on Dynamic Penalty Function. Journal of Deep Space Exploration, 2017, 4(3): 276-280,292 DOI:10.15982/j.issn.2095-7777.2017.03.012

登录浏览全文

4963

注册一个新账户 忘记密码

References

AI Summary AI Mindmap
PDF (681KB)

452

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/