TY - JOUR
T1 - Anti-tangle control of tethered space robots using linear motion of tether offset
AU - Wang, Bingheng
AU - Meng, Zhongjie
AU - Jia, Cheng
AU - Huang, Panfeng
N1 - Publisher Copyright:
© 2019 Elsevier Masson SAS
PY - 2019/6
Y1 - 2019/6
N2 - Removal of uncooperative tumbling targets using tethered space robots is subject to the risk of tether tangling around the targets. A good anti-tangle control should be (1) fuel-saving, (2) implementation-friendly and (3) tether-libration-suppressing. The proposed strategy achieves these requirements by using a linear actuator to move the tether offset. However, the underactuation due to the input constraints and coupling arises as a main technical challenge. We address the issue from the system passivity perspective by constructing the potential energy in terms of the tension torque. This makes the most of the tether characteristic whereby we specify the control objective that steers the target's angular velocity to the tether direction. Then, an energy-based sliding mode motion controller is designed, the parameter of which is optimized using a model predictive controller to satisfy the motion constraint. The tangle-avoidance is further reinforced by adaptively tuning the weight of MPC. A RBF neural network and a extended Kalman filer are also used to render the controller robust to the uncertainties. Simulations with different tumbling rates validate the effectiveness of the method.
AB - Removal of uncooperative tumbling targets using tethered space robots is subject to the risk of tether tangling around the targets. A good anti-tangle control should be (1) fuel-saving, (2) implementation-friendly and (3) tether-libration-suppressing. The proposed strategy achieves these requirements by using a linear actuator to move the tether offset. However, the underactuation due to the input constraints and coupling arises as a main technical challenge. We address the issue from the system passivity perspective by constructing the potential energy in terms of the tension torque. This makes the most of the tether characteristic whereby we specify the control objective that steers the target's angular velocity to the tether direction. Then, an energy-based sliding mode motion controller is designed, the parameter of which is optimized using a model predictive controller to satisfy the motion constraint. The tangle-avoidance is further reinforced by adaptively tuning the weight of MPC. A RBF neural network and a extended Kalman filer are also used to render the controller robust to the uncertainties. Simulations with different tumbling rates validate the effectiveness of the method.
KW - Energy-based control
KW - Model predictive control
KW - Offset control
KW - Tethered space robots
KW - Underactuated systems
UR - http://www.scopus.com/inward/record.url?scp=85064078396&partnerID=8YFLogxK
U2 - 10.1016/j.ast.2019.03.060
DO - 10.1016/j.ast.2019.03.060
M3 - 文章
AN - SCOPUS:85064078396
SN - 1270-9638
VL - 89
SP - 163
EP - 174
JO - Aerospace Science and Technology
JF - Aerospace Science and Technology
ER -