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

Electrical and Computer Engineering

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

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 (US)
Title of host publication	2018 IEEE Conference on Decision and Control, CDC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2810-2815
Number of pages	6
ISBN (Electronic)	9781538613955
DOIs	https://doi.org/10.1109/CDC.2018.8619560
State	Published - Jul 2 2018
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
ISSN (Electronic)	2576-2370

Conference

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

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. (2018). 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). Institute of Electrical and Electronics Engineers Inc.. 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. Institute of Electrical and Electronics Engineers Inc., 2018. 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

Jin, X, Haddad, WM, Jiang, ZP & Vamvoudakis, KG 2018, 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, Institute of Electrical and Electronics Engineers Inc., 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

Jin X, Haddad WM, Jiang ZP, Vamvoudakis KG. Adaptive Control for Mitigating Sensor and Actuator Attacks in Connected Autonomous Vehicle Platoons. In 2018 IEEE Conference on Decision and Control, CDC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 2810-2815. 8619560. (Proceedings of the IEEE Conference on Decision and Control). doi: 10.1109/CDC.2018.8619560

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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

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