Neural Network-Based Distributed Attitude Coordination Control for Spacecraft Formation Flying With Input Saturation


This transient considers the perspective coordination control problem for spacecraft formation flying when solely a subset of the cluster members has access to the common reference angle. A quaternion-primarily based distributed attitude coordination management scheme is proposed with consideration of the input saturation and with the help of the sliding-mode observer, separation principle theorem, Chebyshev neural networks, swish projection algorithm, and strong management technique. Using graph theory and a Lyapunov-based mostly approach, it's shown that the distributed controller will guarantee the angle of all spacecraft to converge to a typical time-varying reference angle when the reference perspective is obtainable only to a portion of the cluster of spacecraft. Numerical simulations are presented to demonstrate the performance of the proposed distributed controller.

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