Solving chance constrained optimal control problems in aerospace via Kernel Density Estimation
2018
Publication type:
Paper in peer-reviewed journals
Journal:
Optimal Control, Applications and Methods, vol. 39(5), pp. 1818-1832
DOI:
HAL:
Keywords :
Optimal control; Aerospace engineering; Kernel Density Estimation; chance constrained optimization; stochastic optimization;
Abstract:
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.
BibTeX:
@article{Cai-Cer-Sas-Tre-Zid-2018,
author={Jean-Baptiste Caillau and Max Cerf and Achille Sassi and
Emmanuel Trélat and Hasnaa Zidani },
title={Solving chance constrained optimal control problems in
aerospace via Kernel Density Estimation },
doi={10.1002/oca.2445 },
journal={Optimal Control, Applications and Methods },
year={2018 },
volume={39(5) },
pages={1818--1832},
}