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Approximate Robust Control of Uncertain Dynamical Systems


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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Dates and versions

hal-01931744 , version 1 (22-11-2018)
hal-01931744 , version 2 (28-02-2019)



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