Resilient Set-based State Estimation for Linear Time-Invariant Systems Using Zonotopes

TL;DR

This paper introduces a resilient set-based state estimation method for LTI systems under sensor attacks, utilizing zonotopes for efficiency and proposing strategies to manage complexity growth, demonstrated on a rotating target system.

Contribution

The paper develops a zonotope-based resilient state estimation approach for LTI systems under sensor attacks, addressing complexity challenges with novel strategies.

Findings

Guaranteed true state containment under certain attack conditions.

Identified exponential complexity growth due to stealthy attacks.

Validated the approach on a rotating target system.

Abstract

This paper considers the problem of set-based state estimation for linear time-invariant (LTI) systems under time-varying sensor attacks. Provided that the LTI system is stable and observable via every single sensor and that at least one sensor is uncompromised, we guarantee that the true state is always contained in the estimated set. We use zonotopes to represent these sets for computational efficiency. However, we show that intelligently designed stealthy attacks may cause exponential growth in the algorithm's worst-case complexity. We present several strategies to handle this complexity issue and illustrate our resilient zonotope-based state estimation algorithm on a rotating target system.