Adaptive artificial potential function guidance for dynamic obstacle avoidance of spacecraft

Peng Gao, Jianjun Luo

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

To avoid the dynamic obstacles during spacecraft autonomous proximity operations, a fuel saving and high-accuracy adaptive artificial potential function guidance method for dynamic obstacles avoidance was presented. As for the situation that the Gaussian repulsive potential function was non-zero at the desired position, a correction term was multiplied to eliminate deviation from the equilibrium point. The guidance law of avoiding dynamic obstacles was deduced based on that of the static obstacles avoidance. Then, according to the relationship between velocity and gravity gradient, the negative feedback control was designed to make the gravity gradient adapt to the variance of velocity, and the adaptive artificial potential function guidance law for dynamic obstacles avoidance was obtained eventually. To verify the correctness and effectiveness of the guidance law, a series of numerical simulations using the precise mathematical model were carried out. The simulation results show that the corrected potential function can effectively improve the convergent precision; and the adaptive artificial potential function guidance law makes the control pulses more reasonable, with saving 30% of the total delta V, and is two degrees more accurate than the traditional artificial potential function guidance law.

Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalZhongguo Kongjian Kexue Jishu/Chinese Space Science and Technology
Volume32
Issue number5
DOIs
StatePublished - Oct 2012

Keywords

  • Adaptive
  • Artificial potential function
  • Dynamic obstacles
  • Guidance
  • Spacecraft

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