4.6 Article

Enhanced rapid attitude stabilization for space robots in postcapture using an iterated extended Kalman filter

期刊

ADVANCES IN SPACE RESEARCH
卷 72, 期 11, 页码 4965-4983

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ELSEVIER SCI LTD
DOI: 10.1016/j.asr.2023.09.023

关键词

Space robot; Rapid stabilization; Uncertainties; Extended Kalman filter

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This paper presents a novel strategy for rapid attitude stabilization of space robots after capturing unknown targets, reducing the impacts of residual momentum, uncertainties in inertial parameters, and observation noise. The approach utilizes dynamical coupling and an iterated extended Kalman filter to estimate the system's motion state and target's inertial parameters. Numerical simulations and Monte Carlo simulations are conducted to verify the validity and feasibility of the approach.
Due to residual momentum, the space robot is tumbling after capturing an unknown target, like space debris because of the law of conservation of momentum. Therefore, it is essential to stabilize the attitude of the base for the objectives such as communication. In addition to the residual momentum and uncertainties in the inertial parameters of the target, the observation noise in real applications would degrade the stabilization performance or even lead to instability. To reduce the impacts of these factors, a novel strategy is presented in this paper for rapid attitude stabilization of space robots in postcapture. This approach exploits the dynamical coupling between the base and the manipulator to stabilize the attitude of the base with the limited control torque. In addition, to mitigate the effects of parameter and measurement uncertainties, an iterated extended Kalman filter is applied to estimate the motion state of the system and inertial parameters of the target in situations with state-dependent measurement noise. To verify the validity and feasibility of the presented approach, numerical simulations have been performed for the 2D and 3D models, and robustness and the effects of observation noise and initial velocity of the base have been analyzed via Monte Carlo simulations. (c) 2023 COSPAR. Published by Elsevier B.V. All rights reserved.

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