By Topic

Adaptive learning control-based periodic trajectory tracking for spacecraft formations

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Hong Wong ; Dept. of Mech., Polytechnic Univ. Brooklyn, New York, NY, USA ; Kapila, V.

This paper addresses a periodic trajectory tracking problem arising in spacecraft formation flying. In particular, the nonlinear position dynamics of a follower spacecraft relative to a leader spacecraft are utilized to develop a learning controller which learns a periodic, unknown model reference control. Using a Lyapunov-based approach, a full state feedback control law, a parameter update algorithm, and a model reference control estimate are designed that facilitate the tracking of given periodic reference trajectories in the presence of unknown leader and follower spacecraft masses. Furthermore, using a discrete Lyapunov-type stability analysis, model reference control error is shown to converge to zero. Illustrative simulations are included to demonstrate the efficacy of the proposed controller.

Published in:

Decision and Control, 2003. Proceedings. 42nd IEEE Conference on  (Volume:4 )

Date of Conference:

9-12 Dec. 2003