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arXiv · 2103.04579

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

Tianci Yang·Carlos Murguia·Chen Lv·Dragan Nesic·Chao Huang
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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.

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Tianci Yang, Carlos Murguia, Chen Lv, Dragan Nesic, Chao Huang. 2021-03-08. On Joint Reconstruction of State and Input-Output Injection Attacks for Nonlinear Systems. https://arxiv.org/abs/2103.04579

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