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Neural network-based distributed attitude coordination control for spacecraft formation flying with input saturation.

An-Min Zou, Krishna Dev Kumar

IEEE Transactions on Neural Networks and Learning Systems

|May 9, 2014

Summary

This study addresses spacecraft formation flying attitude control when not all spacecraft have reference attitude access. A novel distributed control scheme ensures all spacecraft achieve coordinated attitudes, even with partial reference information.

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Area of Science:

Aerospace Engineering
Control Systems Theory
Robotics

Background:

Spacecraft formation flying requires precise attitude coordination.
Limited sensor availability can hinder global attitude synchronization.

Purpose of the Study:

To develop a distributed attitude coordination control scheme for spacecraft formations.
To address challenges where only a subset of spacecraft has access to the common reference attitude.

Main Methods:

A quaternion-based distributed control scheme incorporating input saturation.
Utilized sliding-mode observers, separation principle theorem, Chebyshev neural networks, smooth projection algorithm, and robust control techniques.
Employed graph theory and Lyapunov-based stability analysis.

Main Results:

The proposed distributed controller guarantees attitude convergence for all spacecraft to a common time-varying reference.
The control scheme effectively handles scenarios with partial reference attitude availability.
Demonstrated controller performance through numerical simulations.

Conclusions:

The developed distributed attitude coordination control is effective for spacecraft formations with partial reference access.
The method ensures robust and stable attitude synchronization under input saturation.
Validates the feasibility of achieving coordinated attitudes in complex formation flying scenarios.