A Robust Circle-criterion Observer-based Estimator for Discrete-time Nonlinear Systems in the Presence of Sensor Attacks and Measurement Noise

TL;DR

This paper introduces a robust observer-based estimator for discrete-time nonlinear systems that can withstand sensor attacks and measurement noise, ensuring accurate state estimation and sensor attack isolation.

Contribution

It develops a novel bank of circle-criterion observers for robust state estimation under sensor attacks and noise, including sensor attack isolation algorithms.

Findings

The proposed estimator achieves robustness against sensor attacks and noise.

Simulation results validate the effectiveness of the attack isolation algorithm.

The method extends existing observer designs to handle unbounded attacks and noise.

Abstract

We address the problem of robust state estimation of a class of discrete-time nonlinear systems with positive-slope nonlinearities when the sensors are corrupted by (potentially unbounded) attack signals and bounded measurement noise. We propose an observer-based estimator, using a bank of circle-criterion observers, which provides a robust estimate of the system state in spite of sensor attacks and measurement noise. We first consider the attack-free case where there is measurement noise and we provide a design method for a robust circle-criterion observer. Then, we consider the case when a sufficiently small subset of sensors are subject to attacks and all sensors are affected by measurement noise. We use our robust circle-criterion observer as the main ingredient in building an estimator that provides robust state estimation in this case. Finally, we propose an algorithm for isolating attacked sensors in the case of bounded measurement noise. We test this algorithm through simulations.