This paper presents a new formulation for spacecraft inertia estimation from flight data. Specifically, the inertia estimation problem is formulated as a constrained least squares minimization problem with explicit bounds on the inertia matrix incorporated as LMIs (linear matrix inequalities). The resulting minimization problem is a semidefinite optimization problem that can be solved efficiently with guaranteed convergence to the global optimum by readily available algorithms. This method is applied to test data collected from a robotic testbed consisting of a free rotating body. The results show that the constrained least squares approach produces more accurate estimates of the inertia matrix than standard unconstrained least squares estimation methods.
Spacecraft inertia estimation via constrained least squares
2006 IEEE Aerospace Conference ; 6 pp.
2006-01-01
4270487 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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