SCALABLE DECENTRALIZED NAVIGATION AND CONTROL ALGORITHMS FOR LARGE SCALE SPACECRAFT FORMATIONS
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Abstract
Future NASA missions requiring spacecraft formation flying require an
extremely high level of autonomy and robustness when compared to single
spacecraft systems. This is especially true for formations with a large
number of spacecraft, which naturally have a higher likelihood of
collision, and those that are to be flown in deep space, which are located
too far from the Earth to allow for direct ground-based control. Further,
it is likely that the individual spacecraft will have a limited amount of
resources for sensing and communication. This dissertation is devoted to
the development of decentralized navigation and control algorithms for
such systems. The algorithms developed efficiently utilize the limited
sensing and communication resources at each spacecraft in order to
maintain an accurate estimate of the formation state. Formation keeping
is achieved through the calculation of a reference point which damps noise
in the formation state estimates, of which the reference point is a
function. In the absence of an intra-spacecraft communication subsystem,
optimal sensor switching algorithms are developed which yield accurate
formation state estimates. With communication, individual spacecraft
state estimates are iteratively fused to form formation-optimal state
estimates. Numerical simulations demonstrate the efficacy of these
methods when compared, in terms of fuel usage and formation positioning
error, to an ideal system where each spacecraft has comparatively high
sensing and communication capability.
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NASA JPL
Date Issued
2008-11-05T16:31:10Z
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Keywords
spacecraft; formation; estimation; optimization; scheduling