The parameters optimisation design for variable speed control momentum gyroscopes

Control momentum gyroscopes (CMGs) have many advantages over other actuators for the attitude control of a spacecraft. Compared with the single-gimbal control moment gyroscopes (SGCMGs), the mass and power of the flywheel of variable-speed control moment gyroscopes (VSCMGs) are greatly increased. In...

Full description

Saved in:
Bibliographic Details
Published in:International journal of control Vol. 90; no. 12; p. 2618
Main Authors: Liu, Feng, Zhao, Hui, Yao, Yu, Guo, Yang, Wang, Long
Format: Journal Article
Language:English
Published: Abingdon Taylor & Francis Ltd 01.12.2017
Subjects:
Control moment gyroscopes
Design optimization
Design parameters
Flywheels
Gyroscopes
Laws
Lower bounds
Multiple objective analysis
Product design
Programming
Spacecraft attitude control
Speed control
Steering
ISSN:0020-7179, 1366-5820
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Control momentum gyroscopes (CMGs) have many advantages over other actuators for the attitude control of a spacecraft. Compared with the single-gimbal control moment gyroscopes (SGCMGs), the mass and power of the flywheel of variable-speed control moment gyroscopes (VSCMGs) are greatly increased. In this paper, a new solving strategy of singularity problem is proposed, which concludes the exchangeable momentum and steering law, and the parameters of VSCMGs are designed based on the constraint of singular problem. The configuration characteristics of VSCMGs with the constraint of upper and lower bounds of the flywheel regulation speed are revealed. The steering characteristics of weighted pseudo-inverse with null motion (WPINM) are analysed, then the flywheel torque requirement of WPINM is evaluated based on the geometry theory. At last, the parameter design problem of VSCMGs is cast as multi-objectives and bi-level programming problem. The bi-level programming is transformed into a single-level programming problem by using of the Karush-Kuhn-Tucker condition. Finally, the intelligent algorithm of particle swarm optimisation is presented to solve the nonlinear multi-objective problem.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0020-7179
1366-5820
DOI:10.1080/00207179.2016.1261304