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 |
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Title of host publication | 2018 IEEE Conference on Decision and Control, CDC 2018 |
Pages | 2810-2815 |
Number of pages | 6 |
ISBN (Electronic) | 9781538613955 |
DOIs | |
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 |
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Volume | 2018-December |
ISSN (Print) | 0743-1546 |
Conference
Conference | 57th IEEE Conference on Decision and Control, CDC 2018 |
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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