Robust Adaptive Iterative Learning Control for High-Precision Attitude Tracking of Spacecraft
Publication: Journal of Aerospace Engineering
Volume 34, Issue 1
Abstract
In this paper, a robust adaptive iterative learning control (ILC) scheme is developed for the high-precision attitude tracking control of spacecraft in the presence of parametric uncertainties and external disturbances. The proposed robust adaptive ILC law consists of three parts, i.e., the classic proportional-derivative (PD) feedback control term, the PD-type feedforward learning term, and the robust term. The adaptive updating laws are designed for the gain matrices of both the classic PD feedback control term and the PD-type feedforward learning term. The asymptotic stability of the whole closed-loop system is proved through the Lyapunov function–based convergence analysis. The proposed robust adaptive ILC scheme can not only compensate for the parametric uncertainties and repetitive disturbance, but also handle the nonrepetitive disturbance owing to the robust control concept. Moreover, the proposed robust adaptive ILC scheme can achieve the fast convergence speed benefiting from the adaptive technique. Numerical simulations illustrate the effectiveness and superiority of the proposed ILC scheme.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
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Published In
Journal of Aerospace Engineering
Volume 34 • Issue 1 • January 2021
Copyright
© 2020 American Society of Civil Engineers.
History
Received: May 6, 2020
Accepted: Sep 2, 2020
Published online: Nov 12, 2020
Published in print: Jan 1, 2021
Discussion open until: Apr 12, 2021
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