On Joint Reconstruction of State and Input-Output Injection Attacks for Nonlinear Systems

Tianci Yang, Carlos Murguia, Chen Lv, Dragan Nesic, Chao Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

We address the problem of robust state reconstruction for discrete-time nonlinear systems when the actuators and sensors are injected with (potentially unbounded) attack signals. Exploiting redundancy in sensors and actuators and using a bank of unknown input observers (UIOs), we propose an observer-based estimator capable of providing asymptotic estimates of the system state and attack signals under the condition that the numbers of sensors and actuators under attack are sufficiently small. Using the proposed estimator, we provide methods for isolating the compromised actuators and sensors. Numerical examples are provided to demonstrate the effectiveness of our methods.

Original languageEnglish
Article number9439530
Pages (from-to)554-559
Number of pages6
JournalIEEE Control Systems Letters
Volume6
DOIs
Publication statusPublished - 2022
Externally publishedYes

Keywords

  • actuator attacks
  • cyber-physical systems
  • Nonlinear observers
  • nonlinear systems
  • sensor attacks
  • unknown input observers

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization

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