Solving chance constrained optimal control problems in aerospace via Kernel Density Estimation - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Article Dans Une Revue Optimal Control Applications and Methods Année : 2018

Solving chance constrained optimal control problems in aerospace via Kernel Density Estimation

Résumé

The goal of this paper is to show how non-parametric statistics can be used to solve some chance constrained optimization and optimal control problems. We use the Kernel Density Estimation method to approximate the probability density function of a random variable with unknown distribution , from a relatively small sample. We then show how this technique can be applied and implemented for a class of problems including the God-dard problem and the trajectory optimization of an Ariane 5-like launcher.
Fichier principal
Vignette du fichier
paper_kde.pdf (674.23 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01507063 , version 1 (12-04-2017)

Identifiants

Citer

Jean-Baptiste Caillau, Max Cerf, Achille Sassi, Emmanuel Trélat, Hasnaa Zidani. Solving chance constrained optimal control problems in aerospace via Kernel Density Estimation. Optimal Control Applications and Methods, 2018, 39 (5), pp.1833-1858. ⟨10.1002/oca.2445⟩. ⟨hal-01507063⟩
702 Consultations
962 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More