Resilient path‐following control of autonomous vehicles subject to intermittent denial‐of‐service attacks

Abstract An autonomous vehicle (AV) is a cyber‐physical system (CPS) incorporating dynamics, perception sensors (e.g. camera and radar), embedded electronic control units (ECUs) and in‐vehicle networking (e.g. CAN, LIN and FlexRay).Achieving path‐following control of an AV to track a desired path is...

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Autores principales: Yulei Wang, Ning Bian, Lin Zhang, Yanjun Huang, Hong Chen
Formato: article
Lenguaje:EN
Publicado: Wiley 2021
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Acceso en línea:https://doaj.org/article/1e85a239ce654eaf8d7cde0227669813
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Sumario:Abstract An autonomous vehicle (AV) is a cyber‐physical system (CPS) incorporating dynamics, perception sensors (e.g. camera and radar), embedded electronic control units (ECUs) and in‐vehicle networking (e.g. CAN, LIN and FlexRay).Achieving path‐following control of an AV to track a desired path is therefore a highly non‐linear task that is naturally vulnerable to denial‐of‐service (DoS) attacks. Considering that DoS attacks can inhibit the services of a control system by overwhelming the performance capabilities of the ECUs or the bus, this paper investigates the cyber‐physical system problem of path‐following control for AVs under intermittent DoS attacks. To solve this problem, we propose resilient observer‐based non‐linear control based on the triple‐step approach. The core ideas behind this method are the integrated design of the observer and feedback gains incorporating the DoS duration and the convex design of controller parameters by solving a set of linear matrix inequalities. The proposed control scheme guarantees that the closed‐loop system maintains input‐to‐stable stability, while the error signals theoretically converge to a small neighbourhood of the origin. The effectiveness of the proposed approach is confirmed by the simulation results obtained for a high‐fidelity veDYNA full‐vehicle model with different driving tests and DoS attacks.