This paper aims to investigate the attitude synchronization issue of multi-spacecraft formation flying systems under the limited communication resources.
The authors propose a distributed learning Chebyshev neural network controller (LCNNC) combining a dynamic event-triggered (DET) mechanism and a learning CNN model to achieve accurate multi-spacecraft attitude synchronization under communication constraints.
The proposed method can significantly reduce the internal communication frequency and improve the attitude synchronization accuracy.
This method requires the low communication resources, has a high control accuracy and is thus suitable for engineering applications.
A novel DET mechanism-based LCNNC is proposed to achieve the accurate multi-spacecraft attitude synchronization under communication constraints.
