Journal of Astronautics ›› 2022, Vol. 43 ›› Issue (4): 486-495.doi: 10.3873/j.issn.1000-1328.2022.04.010

Previous Articles     Next Articles

Switching Neural Network Control for Underactuated Spacecraft Formation Reconfiguration

YU Jin long,LI Zhi,ZHANG Ya sheng,DOU Tian heng   

  1. 1. Department of Aerospace Science and Technology,Space Engineering University,Beijing 101400,China;2. Xichang Satellite Launch Center,Wenchang 571300,China
  • Received:2021-05-18 Revised:2021-10-11 Online:2022-04-15 Published:2022-04-15

Abstract: For the formation reconfiguration of underactuated spacecraft in a circular orbit,a switching neural network controller is designed based on the combination of the traditional adaptive neural network controller and the adaptive sliding mode controller to track the optimal open loop control trajectory of spacecraft formation reconstruction solved by the pseudospectral method. The adaptive neural network controller works in the active region and the dynamics uncertainties are approximated by the radial basis function neural networks (RBFNNs). The adaptive sliding mode controller works outside the active region and the upper bound of the approximate error is estimated by the adaptive law. The stability of the closed loop control system is proved via the Lyapunov based approach. The numerical simulation results have demonstrated the rapid,high precision,and robust performance of the proposed controller compared with the linear sliding mode controller.

Key words: Underactuated spacecraft, Switching neural network, Adaptive control, Formation reconfiguration

CLC Number: