6533b861fe1ef96bd12c593f

RESEARCH PRODUCT

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

Emmanuel TrélatAchille SassiMax CerfJean-baptiste CaillauHasnaa Zidani

subject

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]Mathematical optimizationControl and Optimizationchance constrained optimizationKernel density estimation0211 other engineering and technologiesProbability density function02 engineering and technology01 natural sciencesKernel Density Estimation010104 statistics & probability0101 mathematicsMathematics021103 operations researchApplied MathematicsConstrained optimizationTrajectory optimizationstochastic optimizationOptimal controlOptimal controlDistribution (mathematics)Aerospace engineeringControl and Systems EngineeringStochastic optimization[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Random variableSoftware

description

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.

yearjournalcountryeditionlanguage
2017-04-12
https://hal.inria.fr/hal-01507063/document