Attack detection of nonlinear distributed control systems

Xu Zhang, Yang Lu, Minghui Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper considers a class of nonlinear distributed control systems subject to false data injection attacks, Byzantine attacks and switching attacks. The problem of attack detection is formulated as the simultaneous recovery of system states, attack vectors and system mode of a switched nonlinear system. In the proposed attack detection algorithm, the inverse system of each mode aims to estimate system states and attack vectors when the corresponding mode is input-output decoupled. A set-valued mode index map gives all modes which generate a switch-singular pair. A machine learning example is used to validate the performance of the developed algorithm.

Original languageEnglish (US)
Title of host publication2020 American Control Conference, ACC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1459-1464
Number of pages6
ISBN (Electronic)9781538682661
DOIs
StatePublished - Jul 2020
Event2020 American Control Conference, ACC 2020 - Denver, United States
Duration: Jul 1 2020Jul 3 2020

Publication series

NameProceedings of the American Control Conference
Volume2020-July
ISSN (Print)0743-1619

Conference

Conference2020 American Control Conference, ACC 2020
CountryUnited States
CityDenver
Period7/1/207/3/20

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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  • Cite this

    Zhang, X., Lu, Y., & Zhu, M. (2020). Attack detection of nonlinear distributed control systems. In 2020 American Control Conference, ACC 2020 (pp. 1459-1464). [9147765] (Proceedings of the American Control Conference; Vol. 2020-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC45564.2020.9147765