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Neural network-based fixed-time practical attitude synchronization control for uncertain networked spacecraft

Runlong Peng1, Jinchen Ji2, Bin Zheng1

  • 1Shanghai Institute of Applied Mathematics and Mechanics, School of Mechanics and Engineering Science, Shanghai University, Shanghai, 200072, PR China.

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|August 20, 2025
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Summary
This summary is machine-generated.

This study presents a novel fixed-time control scheme using neural networks (NNs) for networked spacecraft systems (NSSs) to achieve practical attitude synchronization despite uncertainties. The method ensures faster convergence and robustness for NSS attitude control.

Keywords:
Fixed-timeNetworked spacecraft systems (NSSs)Neural network (NN)Practical attitude synchronization

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Area of Science:

  • Spacecraft dynamics and control
  • Networked systems
  • Artificial intelligence in control systems

Background:

  • Spacecraft attitude synchronization is crucial for coordinated missions.
  • Existing methods struggle with model uncertainties and external disturbances.
  • Fixed-time control offers finite-time convergence with improved robustness.

Purpose of the Study:

  • To develop a fixed-time practical attitude synchronization scheme for networked spacecraft systems (NSSs).
  • To address model uncertainties and external disturbances using neural networks (NNs).
  • To provide analytical bounds for synchronization error and settling time.

Main Methods:

  • Utilizing Lagrangian representation for spacecraft attitude dynamics.
  • Implementing a fixed-time control strategy enhanced by neural networks.
  • Employing Lyapunov stability analysis for theoretical validation.
  • Deriving analytical expressions for synchronization error and settling time bounds.

Main Results:

  • A novel distributed NN-based fixed-time control scheme was proposed.
  • The scheme ensures practical attitude synchronization for both leaderless and leader-follower NSSs.
  • Analytical derivations confirmed fixed-time stability and provided error/time bounds.
  • Simulations validated the effectiveness and feasibility of the proposed method.

Conclusions:

  • The proposed control scheme effectively achieves fixed-time practical attitude synchronization in NSSs.
  • The integration of NNs enhances adaptability and robustness against uncertainties.
  • The analytical framework provides theoretical guarantees and practical design insights for NSS control.