An Unknown Input Multi-Observer Approach for Estimation, Attack Isolation, and Control of LTI Systems under Actuator Attacks

TL;DR

This paper introduces a novel multi-observer method using Unknown Input Observers to estimate states, detect, and isolate actuator attacks in LTI systems, enhancing system security and resilience.

Contribution

It proposes a new estimator framework that leverages a bank of UIOs for exponential state and attack signal estimation under limited actuator attacks.

Findings

Effective attack detection and isolation demonstrated in simulations

Exponential convergence of state and attack estimates

Robust control performance under actuator attacks

Abstract

We address the problem of state estimation, attack isolation, and control for discrete-time Linear Time Invariant (LTI) systems under (potentially unbounded) actuator false data injection attacks. Using a bank of Unknown Input Observers (UIOs), each observer leading to an exponentially stable estimation error in the attack-free case, we propose an estimator that provides exponential estimates of the system state and the attack signals when a sufficiently small number of actuators are attacked. We use these estimates to control the system and isolate actuator attacks. Simulations results are presented to illustrate the performance of the results.