We address the problem of state estimation and attack isolation for general discrete-time nonlinear systems when sensors are corrupted by (potentially unbounded) attack signals. For a large class of nonlinear plants and observers, we provide a general estimation scheme, built around the idea of sensor redundancy and multi-observer, capable of reconstructing the system state in spite of sensor attacks and noise. This scheme has been proposed by others for linear systems/observers and here we propose a unifying framework for a much larger class of nonlinear systems/observers. Using the proposed estimator, we provide an isolation algorithm to pinpoint attacks on sensors during sliding time windows. Simulation results are presented to illustrate the performance of our tools.
@article{arxiv.1904.04236,
title = {A Multi-Observer Based Estimation Framework for Nonlinear Systems under Sensor Attacks},
author = {Tianci Yang and Carlos Murguia and Margreta Kuijper and Dragan Nesic},
journal= {arXiv preprint arXiv:1904.04236},
year = {2019}
}
Comments
arXiv admin note: text overlap with arXiv:1806.06484