Adaptive Control for Mitigating Sensor and Actuator Attacks in Connected Autonomous Vehicle Platoons

Xu Jin; Wassim M. Haddad; Zhong Ping Jiang; Kyriakos G. Vamvoudakis

doi:10.1109/CDC.2018.8619560

Adaptive Control for Mitigating Sensor and Actuator Attacks in Connected Autonomous Vehicle Platoons

Xu Jin, Wassim M. Haddad, Zhong Ping Jiang, Kyriakos G. Vamvoudakis

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

In this paper, we develop an adaptive control algorithm for addressing security for a class of networked vehicles that comprise n human-driven vehicles sharing kinematic data and an autonomous vehicle in the aft of the vehicle formation receiving data from the preceding vehicles by wireless vehicle-to-vehicle communication devices. Specifically, we develop an adaptive controller for mitigating time-invariant, state-dependent adversarial sensor and actuator attacks while guaranteeing uniform ultimate boundedness of the closed-loop networked system. The effectiveness of the proposed approach is demonstrated by an illustrative numerical example involving a platoon of connected vehicles.

Original language	English
Title of host publication	2018 IEEE Conference on Decision and Control, CDC 2018
Pages	2810-2815
Number of pages	6
ISBN (Electronic)	9781538613955
DOIs	https://doi.org/10.1109/CDC.2018.8619560
State	Published - Jan 18 2019
Event	57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States Duration: Dec 17 2018 → Dec 19 2018

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	2018-December
ISSN (Print)	0743-1546

Conference

Conference	57th IEEE Conference on Decision and Control, CDC 2018
Country/Territory	United States
City	Miami
Period	12/17/18 → 12/19/18

Bibliographical note

Funding Information:
This work was supported in part by the Air Force Office of Scientific Research under Grant FA9550-16-1-0100, NSF under Grant ECCS-1501044, NATO under Grant SPS G5176, ONR under Minerva Grant N00014-18-1-2160, and NAWCAD under Grant N00421-16-2-0001.

Funding Information:
This work was supported in part by the Air Force Office of Scientific Research under Grant FA9550-16-1-0100, NSF under Grant ECCS-1501044, NATO under Grant SPS G5176, ONR under Minerva Grant N00014-18-1- 2160, and NAWCAD under Grant N00421-16-2-0001.

Publisher Copyright:
© 2018 IEEE.

ASJC Scopus subject areas

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

Access to Document

10.1109/CDC.2018.8619560

Cite this

Jin, X., Haddad, W. M., Jiang, Z. P., & Vamvoudakis, K. G. (2019). Adaptive Control for Mitigating Sensor and Actuator Attacks in Connected Autonomous Vehicle Platoons. In 2018 IEEE Conference on Decision and Control, CDC 2018 (pp. 2810-2815). Article 8619560 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2018-December). https://doi.org/10.1109/CDC.2018.8619560

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abstract = "In this paper, we develop an adaptive control algorithm for addressing security for a class of networked vehicles that comprise n human-driven vehicles sharing kinematic data and an autonomous vehicle in the aft of the vehicle formation receiving data from the preceding vehicles by wireless vehicle-to-vehicle communication devices. Specifically, we develop an adaptive controller for mitigating time-invariant, state-dependent adversarial sensor and actuator attacks while guaranteeing uniform ultimate boundedness of the closed-loop networked system. The effectiveness of the proposed approach is demonstrated by an illustrative numerical example involving a platoon of connected vehicles.",

author = "Xu Jin and Haddad, {Wassim M.} and Jiang, {Zhong Ping} and Vamvoudakis, {Kyriakos G.}",

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Jin, X, Haddad, WM, Jiang, ZP & Vamvoudakis, KG 2019, Adaptive Control for Mitigating Sensor and Actuator Attacks in Connected Autonomous Vehicle Platoons. in 2018 IEEE Conference on Decision and Control, CDC 2018., 8619560, Proceedings of the IEEE Conference on Decision and Control, vol. 2018-December, pp. 2810-2815, 57th IEEE Conference on Decision and Control, CDC 2018, Miami, United States, 12/17/18. https://doi.org/10.1109/CDC.2018.8619560

Adaptive Control for Mitigating Sensor and Actuator Attacks in Connected Autonomous Vehicle Platoons. / Jin, Xu; Haddad, Wassim M.; Jiang, Zhong Ping et al.
2018 IEEE Conference on Decision and Control, CDC 2018. 2019. p. 2810-2815 8619560 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2018-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In this paper, we develop an adaptive control algorithm for addressing security for a class of networked vehicles that comprise n human-driven vehicles sharing kinematic data and an autonomous vehicle in the aft of the vehicle formation receiving data from the preceding vehicles by wireless vehicle-to-vehicle communication devices. Specifically, we develop an adaptive controller for mitigating time-invariant, state-dependent adversarial sensor and actuator attacks while guaranteeing uniform ultimate boundedness of the closed-loop networked system. The effectiveness of the proposed approach is demonstrated by an illustrative numerical example involving a platoon of connected vehicles.

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Adaptive Control for Mitigating Sensor and Actuator Attacks in Connected Autonomous Vehicle Platoons

Abstract

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