Time-optimal reorientation using neural network and particle swarm formulation

Ko Basu, Robert Graham Melton, Sarah Aguasvivas-Manzano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A neural network will be developed to supplement a particle swarm algorithm to find near-minimum-time reorientation maneuvers in the presence of path constraints. The method employs a quaternion formulation of the kinematics, using B-splines to represent the quaternions. Dynamic Inversion will be used in the supervised training of the neural network.

Original languageEnglish (US)
Title of host publicationASTRODYNAMICS 2017
PublisherUnivelt Inc.
Pages233-246
Number of pages14
Volume162
ISBN (Print)9780877036456
Publication statusPublished - Jan 1 2018
EventAAS/AIAA Astrodynamics Specialist Conference, 2017 - Stevenson, United States
Duration: Aug 20 2017Aug 24 2017

Other

OtherAAS/AIAA Astrodynamics Specialist Conference, 2017
CountryUnited States
CityStevenson
Period8/20/178/24/17

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All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science

Cite this

Basu, K., Melton, R. G., & Aguasvivas-Manzano, S. (2018). Time-optimal reorientation using neural network and particle swarm formulation. In ASTRODYNAMICS 2017 (Vol. 162, pp. 233-246). Univelt Inc..