Using genetic algorithm to solve the parameters optimization problem of space maneuver vehicle rapidly approaching sub-orbit target

Qiyu Wang; Jianping Yuan; Zhanxia Zhu

doi:10.1117/12.775023

10 November 2007 Using genetic algorithm to solve the parameters optimization problem of space maneuver vehicle rapidly approaching sub-orbit target

Qiyu Wang, Jianping Yuan, Zhanxia Zhu

Author Affiliations +

Proceedings Volume 6795, Second International Conference on Space Information Technology; 67955O (2007) https://doi.org/10.1117/12.775023
Event: Second International Conference on Spatial Information Technology, 2007, Wuhan, China

Abstract

In this paper, we research a convenient method and its mathematics model of using space maneuver vehicle (SMV) rapidly approach sub-orbit target. For minimizing the velocity impulse needs by the transfer orbit, an object function is set up. Then we use a genetic algorithm toolbox GAOT to get the optimal result of this object function. Last, we simulate the two situations; including the SMV's orbit parameters are known or unknown. These simulation results show that this method can be used to find the rapidly approaching orbit which needs the minimal velocity impulse.

Citation Download Citation

Qiyu Wang, Jianping Yuan, and Zhanxia Zhu "Using genetic algorithm to solve the parameters optimization problem of space maneuver vehicle rapidly approaching sub-orbit target", Proc. SPIE 6795, Second International Conference on Space Information Technology, 67955O (10 November 2007); https://doi.org/10.1117/12.775023

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available