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Communication Dans Un Congrès Année : 2022

A Real-Time NMPC Controller for Autonomous Vehicle Racing

Contrôleur NMPC temps réel pour course de véhicules autonomes

Résumé

Non-linear model predictive control (NMPC) solves structured optimization problems under predetermined constraints. It results in an optimal control series in a multiple-step prediction horizon. However, the NMPC requires considerable computation time, making it difficult to implement on devices with limited resources. We focus on an NMPC-based controller used for autonomous vehicle racing. It is a typical representative of quickly evolving cyber-physical systems. In the single-vehicle racing mode, we propose a triggering method to enable the execution of long-horizon NMPC, which is desirable for achieving a better lap time. For the head-to-head racing mode, in order to react rapidly to the evolving surroundings, we propose a short-horizon NMPC-based control strategy with safe overtaking capability. These control strategies can be implemented within a limited time budget.
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Dates et versions

hal-04009646 , version 1 (01-03-2023)

Identifiants

Citer

Nan Li, Eric Goubault, Laurent Pautet, Sylvie Putot. A Real-Time NMPC Controller for Autonomous Vehicle Racing. 2022 6th International Conference on Automation, Control and Robots (ICACR), Sep 2022, Shanghai, China. pp.148-155, ⟨10.1109/ICACR55854.2022.9935523⟩. ⟨hal-04009646⟩
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