Neural-network-based adaptive quantized attitude takeover control of spacecraft by using cellular satellites

Abstract

The problem of attitude takeover control of spacecraft by using cellular satellites with the limited inter-satellite communication capacity, the unknown inertia matrix and external disturbances is studied. A hysteresis quantizer is employed to quantize the signal of control torque generated by the controller cellular satellite. The signal of quantized control torque is transmitted to the actuator cellular satellites only when the quantization signal changes, which can greatly reduce the communication burden between the controller cellular satellite and the actuator cellular satellites. To approximate the unknown attitude dynamics of the spacecraft, the radial basis function neural network is introduced. Furthermore, a distributed control allocation strategy is proposed to deal with the control allocation problem for the actuator cellular satellites with faults. Lastly, the effectiveness of the proposed scheme is validated by numerical simulations.