An Unknown Input Multi-Observer Approach for Estimation and Control under Adversarial Attacks

TL;DR

This paper introduces a robust observer-based estimation and control method for linear systems under false data injection attacks, leveraging unknown input observers and redundancy to ensure stability and attack isolation.

Contribution

It proposes a novel multi-observer approach that guarantees exponential state estimation and attack isolation despite unbounded actuator and sensor attacks.

Findings

Effective attack detection and isolation demonstrated in simulations

Ensures system stability by switching off compromised actuators

Works with a small subset of sensors and actuators under attack

Abstract

We address the problem of state estimation, attack isolation, and control of discrete-time linear time-invariant systems under (potentially unbounded) actuator and sensor false data injection attacks. Using a bank of unknown input observers, each observer leading to an exponentially stable estimation error (in the attack-free case), we propose an observer-based estimator that provides exponential estimates of the system state in spite of actuator and sensor attacks. Exploiting sensor and actuator redundancy, the estimation scheme is guaranteed to work if a sufficiently small subset of sensors and actuators are under attack. Using the proposed estimator, we provide tools for reconstructing and isolating actuator and sensor attacks; and a control scheme capable of stabilizing the closed-loop dynamics by switching off isolated actuators. Simulation results are presented to illustrate the performance of our tools.