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

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.
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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 Appl. Methods, Wiley, 2018, 39 (5), pp.1833-1858. ⟨10.1002/oca.2445⟩. ⟨hal-01507063⟩

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