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Approximate Robust Control of Uncertain Dynamical Systems

Edouard Leurent 1, 2, 3 Yann Blanco 3 Denis Efimov 2 Odalric-Ambrym Maillard 1
1 SEQUEL - Sequential Learning
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : This work studies the design of safe control policies for large-scale non-linear systems operating in uncertain environments. In such a case, the robust control framework is a principled approach to safety that aims to maximize the worst-case performance of a system. However, the resulting optimization problem is generally intractable for non-linear systems with continuous states. To overcome this issue, we introduce two tractable methods that are based either on sampling or on a conservative approximation of the robust objective. The proposed approaches are applied to the problem of autonomous driving.
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Preprints, Working Papers, ...
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https://hal.archives-ouvertes.fr/hal-01931744
Contributor : Edouard Leurent <>
Submitted on : Thursday, February 28, 2019 - 8:17:16 PM
Last modification on : Wednesday, October 14, 2020 - 3:40:49 AM
Long-term archiving on: : Wednesday, May 29, 2019 - 5:45:44 PM

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  • HAL Id : hal-01931744, version 2
  • ARXIV : 1903.00220

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Edouard Leurent, Yann Blanco, Denis Efimov, Odalric-Ambrym Maillard. Approximate Robust Control of Uncertain Dynamical Systems. 2019. ⟨hal-01931744v2⟩

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