Chance constrained optimization of a three-stage launcher

Journées SMAI-MODE 2016 (Toulouse)

Kernel Density Estimation applied to the chance-constrained Goddard problem

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

International audience; 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.

Optimisation d’un lanceur