Minimum-Time Spacecraft Attitude Motion Planning Using Objective Alternation in Derivative-Free Optimization

Fabio Celani () and Renato Bruni ()
Additional contact information
Fabio Celani: Sapienza University of Rome
Renato Bruni: Sapienza University of Rome

Journal of Optimization Theory and Applications, 2021, vol. 191, issue 2, No 18, 776-793

Abstract: Abstract This work presents an approach to spacecraft attitude motion planning which guarantees rest-to-rest maneuvers while satisfying pointing constraints. Attitude is represented on the group of three dimensional rotations. The angular velocity is expressed as weighted sum of some basis functions, and the weights are obtained by solving a constrained minimization problem in which the objective is the maneuvering time. However, the analytic expressions of objective and constraints of this minimization problem are not available. To solve the problem despite this obstacle, we propose to use a derivative-free approach based on sequential penalty. Moreover, to avoid local minima traps during the search, we propose to alternate phases in which two different objective functions are pursued. The control torque derived from the spacecraft inverse dynamics is continuously differentiable and vanishes at its endpoints. Results on practical cases taken from the literature demonstrate advantages over existing approaches.

Keywords: Attitude motion planning; Pointing constraints; Derivative-free optimization; Objective perturbation; Slepian functions; 49M37; 90C26; 90C90 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10957-021-01834-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:191:y:2021:i:2:d:10.1007_s10957-021-01834-x

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

DOI: 10.1007/s10957-021-01834-x

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().