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Dynamic path planning and trajectory tracking using MPC for satellite with collision avoidance.

Qinglei Hu1, Jingjie Xie1, Chenliang Wang1

  • 1School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.

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|October 15, 2018
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Summary
This summary is machine-generated.

This study introduces a new algorithm for autonomous satellite path planning and trajectory tracking, ensuring smooth, fuel-efficient movement around space station obstacles. The method guarantees stability and demonstrates effectiveness in simulations for complex space missions.

Keywords:
B-splineModel predictive controlObstacles avoidancePath planningTrajectory tracking

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Area of Science:

  • Aerospace Engineering
  • Robotics
  • Control Systems

Background:

  • Autonomous satellites require precise path planning and trajectory tracking for space missions.
  • Space station environments present geometric channel constraints and obstacle avoidance challenges.
  • Smooth trajectories are crucial to prevent satellite stoppages at waypoints.

Purpose of the Study:

  • To develop a dynamic path planning and trajectory tracking algorithm for autonomous satellites.
  • To address geometric channel constraints and ensure smooth, continuous curvature trajectories.
  • To optimize fuel consumption and ensure closed-loop stability during space tasks.

Main Methods:

  • Utilizing a 3D B-spline template to minimize path curvature and ensure continuity.
  • Employing a novel projection method to solve for reference states and inputs.
  • Implementing a finite horizon model predictive control (MPC) for trajectory tracking.
  • Ensuring stability through a feedback controller, terminal penalty, and terminal constraint set.

Main Results:

  • The proposed algorithm effectively plans dynamic paths and tracks trajectories for autonomous satellites.
  • B-spline templates ensure smooth, continuous curvature, avoiding waypoint discontinuities.
  • The MPC method optimizes performance by minimizing fuel consumption while respecting constraints.
  • Simulation experiments validate the algorithm's effectiveness and practicality in complex scenarios.

Conclusions:

  • The developed algorithm offers a robust solution for autonomous satellite navigation in constrained environments.
  • The combination of B-splines and MPC provides smooth, fuel-efficient, and stable trajectory control.
  • This approach enhances the capability of autonomous satellites for performing complex space tasks.