Journal of Astronautics ›› 2019, Vol. 40 ›› Issue (6): 684-693.

### Adaptive Sliding Mode Control Based on Neural Network for Approaching to an Uncontrolled Tumbling Satellite

LIU Jiang hui，LI Hai yang

1. College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China
• Received:2018-05-08 Revised:2018-09-17 Online:2019-06-15 Published:2019-06-25

Abstract:

For the situation that an uncontrolled spacecraft is tumbling freely in space, the six-degree-of-freedom coupled control problem of the chaser’s approach to the uncontrolled tumbling target is studied. An integrated dynamic model of attitude and orbit for the relative motion between the chaser and the target is established; besides，the nominal trajectory and nominal attitude of the chaser’s approaching process are designed. With considering the coupled factors of the system uncertainties and external disturbances, an adaptive fuzzy sliding mode controller without chattering is designed. A neural network adaptive sliding mode controller without chattering is designed. The sliding mode control is combined with the neural network approximation, and the unknown part of the system is adaptively approximated by the radical basis function (RBF) neural network. The neural network adaptive law is derived through the Lyapunov method, and the stability of the entire closed-loop system is guaranteed by adjusting the adaptive weights. The numerical simulation example demonstrates the rationality of the designed nominal trajectory and nominal attitude. At the same time, it verifies the effectiveness of the neural network adaptive sliding mode controller.

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