Semianalytical Bounded Formation Configuration Screening Method Based on Poincaré Contraction Mapping

This paper proposes a semi-analytical method combining Poincaré Contraction Mapping (PCM) with Conditional Variational Autoencoder (CVAE) for efficient screening of bounded relative orbit across perturbed environments. The PCM projects high-dimensional system parameters to a two-dimensional (2D) feature parameter pair of crossing period and separation angle, which is surjective but non-injective. To address the one-to-many inverse mapping challenge, a CVAE-based deep learning model is developed to raise the dimensionality from the 2D feature parameters back to the state space, enabling rapid and diverse generation of long-duration relative orbits with bounded amplitude. And the PCM-CVAE method is validated in…

• NN
  National Natural Science Foundation of China

  Award: 124B2048