ETLBO based optimal targeting to the moon in the PCR3BP chaotic system

Yang Wang, Binfeng Pan, Yue Zheng and Xiang Lu

Chaos, Solitons & Fractals, 2017, vol. 105, issue C, 21-28

Abstract: The chaotic transport in Earth-Moon three-body system has been demonstrated to be a novel approach to explore the Moon at a low energy cost. However, existing targeting methods require sufficient experience to construct Earth-Moon chaotic transfer orbits, which is not an easy task to the untrained eye. In this paper, the elitist teaching-learning-based optimization (ETLBO) based optimal targeting method is presented to provide a systematic approach to design the chaotic transfer orbits in the Earth-Moon planar circular restricted three-body problem, without any requirement of prior experience. Unlike the existing targeting methods, the chaotic transfer orbits design problem is treated as a class of multi-constraints fuel-optimal problem with multi-dimensional decision variables. A discrete chaotic dynamical model is formulated according to the Poincaré map, and several consecutive control steps of small bounded thrusts are made to direct the chaotic series towards the desired invariant torus near the Moon. The suboptimal consecutive control thrusts are obtained by a state-of-art numerical optimization algorithm ETLBO, which does not require any algorithm-specific parameters with less computational effort. Numerical demonstrates are provided to illustrate the applications of the ETLBO based optimal targeting method, which reveal that several potential chaotic transfer orbits can be easily obtained by this method.

Keywords: Chaos control; Teaching-learning-based optimization; Earth-Moon transfer; Optimal targeting (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:105:y:2017:i:c:p:21-28

DOI: 10.1016/j.chaos.2017.10.009

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