Free Floating Space Manipulator Control Based on Bi-LSTM Networks

To solve the problem of trajectory tracking control for free floating space manipulator with model uncertainties and external disturbances, a neural network based adaptive sliding mode controller is proposed. To address the model uncertainty, the bidirectional long short term memory neural network (Bi-LSTM) is employed to estimate the uncertainty of the space manipulator model through offline learning. The adaptive sliding mode control is adopted to handle the estimation errors of neural network and external disturbances. The stability of the proposed controller is analyzed via Lyapunov theory. Numerical simulations verify the effectiveness of the proposed control strategy. The results show that the proposed novel controller can effectively improve the control performance at low gains.