Finite-Time Secure Dynamic State Estimation for Cyber–Physical Systems Under Unknown Inputs and Sensor Attacks

TLDR

Cyber‑attacks on sensor nodes can corrupt local finite‑time state estimators. The paper proposes an efficient finite‑time secure dynamic state estimation method for CPSs with unknown inputs and cyber‑attacks. The method employs local finite‑time estimators on sensor subsets, a detection algorithm to select attack‑free estimators, and then fuses their outputs for secure state estimation and attack localization. Analytical conditions for feasibility and finite‑time convergence are derived, and the approach is validated on a dc electric motor and software‑in‑the‑loop tests, confirming real‑time feasibility.

Abstract

In this article, an efficient method for finite-time secure dynamic state estimation in cyber–physical systems (CPSs) subjected to unknown inputs and cyber-attacks is proposed. The proposed approach is based on a set of local finite-time state estimators operating over the subsets of sensory nodes, which are designed to estimate the states of the CPS subjected to unknown inputs. When cyber-attacks compromise some sensory nodes, the estimation results of the local finite-time estimators which use the measurements of the attacked sensors can be corrupted. An efficient detection algorithm is thus proposed to identify the valid local estimators that are completely devoid of the attacked sensory nodes. The information of the valid local estimators is then used to achieve secure state estimation and localization of the launched cyber-attack. The necessary and sufficient conditions for the feasibility and finite-time convergence of the proposed estimation mechanism are analytically derived and proven. The effectiveness of the proposed method is demonstrated by testing it on a dc electric motor. Likewise, some online software-in-the-loop tests are conducted to demonstrate the real-time feasibility of the proposed algorithm.