Convergence rates for ensemble-based solutions to optimal control of uncertain dynamical systems

Fuente: arXiv
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Main Authors: Melnikov, Olena, Milz, Johannes
Format: Preprint
Published: 2024
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author Melnikov, Olena
Milz, Johannes
author_facet Melnikov, Olena
Milz, Johannes
contents We consider optimal control problems involving nonlinear ordinary differential equations with uncertain inputs. Using the sample average approximation, we obtain optimal control problems with ensembles of deterministic dynamical systems. Leveraging techniques for metric entropy bounds, we derive non-asymptotic Monte Carlo-type convergence rates for the ensemble-based solutions. Our theoretical framework is validated through numerical simulations on a harmonic oscillator problem and a vaccination scheduling problem for epidemic control under model parameter uncertainty.
format Preprint
id arxiv_https___arxiv_org_abs_2407_18182
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Convergence rates for ensemble-based solutions to optimal control of uncertain dynamical systems
Melnikov, Olena
Milz, Johannes
Optimization and Control
90C15, 90C30, 49K45, 49N60
We consider optimal control problems involving nonlinear ordinary differential equations with uncertain inputs. Using the sample average approximation, we obtain optimal control problems with ensembles of deterministic dynamical systems. Leveraging techniques for metric entropy bounds, we derive non-asymptotic Monte Carlo-type convergence rates for the ensemble-based solutions. Our theoretical framework is validated through numerical simulations on a harmonic oscillator problem and a vaccination scheduling problem for epidemic control under model parameter uncertainty.
title Convergence rates for ensemble-based solutions to optimal control of uncertain dynamical systems
topic Optimization and Control
90C15, 90C30, 49K45, 49N60
url https://arxiv.org/abs/2407.18182