Online One-Step Parameter Identification Method for a Space Robot with Initial Momentum in Postcapture
Publication: Journal of Aerospace Engineering
Volume 33, Issue 4
Abstract
For precise attitude control of space robots intended to capture a target, the inertial parameters of the target need to be well estimated because the motions of arms and bases are coupled. This paper presents a momentum-based, online, one-step identification method for estimating inertial parameters of tumbling targets with linear momentum by space robots after capture. For obtaining the target’s mass and mass center, the method is the same as the traditional momentum-based method, while two contributions are made for identifying inertia tensor. The first contribution is the second-order term in the identification equation is written as the product of two functions: function of time and function of mass and mass center of the target. Secondly, the traditional recursive least squares (RLS) method is modified to obtain the corresponding inertia tensor without iteration from the beginning. To verify the validity and feasibility of the proposed identification technique, 2D and 3D models with different targets and initial velocities are both simulated and analyzed. The simulation results show that all the estimated values converge to their ideal values and the method can be easily achieved online via recursive techniques.
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Data Availability Statement
Some data during the study are available from the corresponding author by request, including parameters of the models and simulation results.
Acknowledgments
This paper has been financially supported by National Natural Science Foundation of China [Grant Nos. 11402200 and 11502203] and the China Scholarship Council (CSC). Teng Zhang would like to thank Dr. Sameoto from the University of Alberta for providing language help.
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Published In
Journal of Aerospace Engineering
Volume 33 • Issue 4 • July 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Jan 9, 2018
Accepted: Nov 15, 2019
Published online: Apr 17, 2020
Published in print: Jul 1, 2020
Discussion open until: Sep 17, 2020
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