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This study presents optimal cooperative control algorithms for spacecraft formation flying, ensuring collision avoidance and trajectory tracking. The methods guarantee system stability and optimal performance using local information.

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Area of Science:

  • Aerospace Engineering
  • Control Theory
  • Robotics

Background:

  • Spacecraft formation flying requires precise control for mission success.
  • Collision avoidance is a critical safety concern in multi-spacecraft systems.
  • Existing control algorithms may lack optimality or rely on global information.

Purpose of the Study:

  • To develop optimal cooperative control algorithms for spacecraft formation flying.
  • To ensure collision avoidance between spacecraft within a formation.
  • To achieve precise trajectory tracking and optimal formation performance.

Main Methods:

  • Utilizing potential functions for collision avoidance.
  • Constructing index cost functions for optimal control.
  • Applying state-dependent Riccati equations for control algorithm design.
  • Employing Lyapunov stability theory for system analysis.

Main Results:

  • The proposed algorithms guarantee collision avoidance for the formation.
  • Spacecraft formations can track reference trajectories accurately.
  • The control system achieves optimal performance states.
  • Lyapunov stability analysis confirms the asymptotic stability of the closed-loop system.

Conclusions:

  • The developed optimal cooperative control algorithms are effective for spacecraft formation flying.
  • The algorithms ensure both safety (collision avoidance) and performance (trajectory tracking, optimality).
  • The use of local information vectors enhances the practicality of the control approach.