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Iterative model and trajectory refinement for orbital trajectory optimization
Author(s) -
Hudson Jennifer,
Gupta Rohit,
Li Nan,
Kolmanovsky Ilya
Publication year - 2017
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2319
Subject(s) - trajectory optimization , trajectory , nonlinear system , optimal control , mathematical optimization , convergence (economics) , quadratic equation , computer science , mathematics , control theory (sociology) , control (management) , physics , artificial intelligence , geometry , quantum mechanics , astronomy , economics , economic growth
Summary An iterative model and trajectory refinement (IMTR) strategy is proposed for trajectory optimization of nonlinear systems. A high‐ and a low‐fidelity models are used. The high‐fidelity model accurately represents the system but is not easily amenable to trajectory optimization, because of degree of nonlinearity, computational cost, or to being of “black‐box” type. The low‐fidelity model is suitable for numerical optimization but approximates the system dynamics with an error. The IMTR method is proposed to systematically iterate between the 2 models and efficiently converge on a control solution. Examples are drawn from orbital mechanics. The IMTR approach is compared to optimal nonlinear quadratic control using Pontryagin maximum principle. A convergence criterion for the IMTR iterations is established.