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.