Modeling Hubble Space Telescope flight data by Q-Markov cover identification
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This paper presents a state-space model for the Hubble space telescope under the influence of unknown disturbances in orbit. This model was obtained from flight data by applying the g-Markov Covariance Equivalent Realization (g-Markov Cover) identification algorithm. This state-space model guarantees the match of the first g-Markov parameters and covariance parameters of the Hubble system. The flight data were partitioned into high- and low-frequency components for more efficient Q-Markov Cover modeling to reduce some computational difficulties of the g-Markov Cover algorithm. This identification revealed more than 20 lightly damped modes within the bandwidth of the attitude control system. Comparisons with the analytical (TREETOPS) model are also included. © 1994 American Institute of Aeronautics and Astronautics, Inc., All rights reserved.
author list (cited authors)
Liu, K., Skelton, R. E., & Sharkey, J. P.