Trajectory tracking control of space robots in task space is of great importance to space missions, which require on-orbit manipulations. This paper focuses on position and attitude tracking control of a tree-floating...Trajectory tracking control of space robots in task space is of great importance to space missions, which require on-orbit manipulations. This paper focuses on position and attitude tracking control of a tree-floating space robot in task space. Since nei- ther the nonlinear terms and parametric uncertainties of the dynamic model, nor the external disturbances are known, an adap- tive radial basis function network based nonsingular terminal sliding mode （RBF-NTSM） control method is presented. The proposed algorithm combines the nonlinear sliding manifold with the radial basis function to improve control performance. Moreover, in order to account for actuator physical constraints, a constrained adaptive RBF-NTSM, which employs a RBF network to compensate for the limited input is developed. The adaptive updating laws acquired by Lyapunov approach guar- antee the global stability of the control system and suppress chattering problems. Two examples are provided using a six-link free-floating space robot. Simulation results clearly demonstrate that the proposed constrained adaptive RBF-NTSM control method performs high precision task based on incomplete dynamic model of the space robots. In addition, the control errors converge faster and the chattering is eliminated comparing to traditional sliding mode control.展开更多
文摘Trajectory tracking control of space robots in task space is of great importance to space missions, which require on-orbit manipulations. This paper focuses on position and attitude tracking control of a tree-floating space robot in task space. Since nei- ther the nonlinear terms and parametric uncertainties of the dynamic model, nor the external disturbances are known, an adap- tive radial basis function network based nonsingular terminal sliding mode （RBF-NTSM） control method is presented. The proposed algorithm combines the nonlinear sliding manifold with the radial basis function to improve control performance. Moreover, in order to account for actuator physical constraints, a constrained adaptive RBF-NTSM, which employs a RBF network to compensate for the limited input is developed. The adaptive updating laws acquired by Lyapunov approach guar- antee the global stability of the control system and suppress chattering problems. Two examples are provided using a six-link free-floating space robot. Simulation results clearly demonstrate that the proposed constrained adaptive RBF-NTSM control method performs high precision task based on incomplete dynamic model of the space robots. In addition, the control errors converge faster and the chattering is eliminated comparing to traditional sliding mode control.
