Orbital transfers: optimization methods      and recent results

Mauro Pontani

doi:10.3934/naco.2011.1.435

Article Contents

2011, Volume 1, Issue 3: 435-485. Doi: 10.3934/naco.2011.1.435

This issue Previous Article Continuity of second-order adjacent derivatives for weak perturbation maps in vector optimization Next Article A note on monotone approximations of minimum and maximum functions and multi-objective problems

Orbital transfers: optimization methods and recent results

Mauro Pontani^1,

1.
Scuola di Ingegneria Aerospaziale -- University of Rome "La Sapienza", via Salaria 851, 00138 Rome

Received: April 2011

Revised: July 2011

Published: August 2011

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Abstract

A wide variety of techniques have been employed in the past for optimizing orbital transfers, which represent the trajectories that lead a spacecraft from a given initial orbit to a specified final orbit. This paper describes several original approaches to optimizing impulsive and finite--thrust orbital transfers, and presents some very recent results. First, impulsive transfers between Keplerian trajectories are considered. A new, analytical optimization method applied to these transfers leads to conclusions of a global nature for transfers involving both ellipses and escape trajectories, without any limitation on the number of impulses, and with possible constraints on the radius of closest approach and greatest recession from the attracting body. A direct optimization technique, termed direct collocation with nonlinear programming algorithm, is then applied to finite--thrust transfers between circular orbits. Lastly, low--thrust orbital transfers are optimized through the joint use of the necessary conditions for optimality and of the recently introduced heuristic method referred to as particle swarm optimization. This work offers a complete description and demonstrates the effectiveness of the distinct techniques applied to optimizing orbital transfer problems of different nature.

Keywords:

Orbital Transfers,
direct collocation with nonlinear programming,
particle swarm optimization.

Mathematics Subject Classification: Primary: 58F15, 58F17; Secondary: 53C35.

Citation:

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