Cyberattack Detection, Fault Estimation, and Fault‐Tolerant Control of Smart‐Grid Cyber‐Physical Systems

ABSTRACT This paper addresses the problem of joint detection and estimation of cyberattacks and physical faults in smart‐grid cyber‐physical systems. In practical smart‐grid environments, physical faults arising from equipment degradation may coexist with malicious cyber threats, leading to significant degradation in system reliability and operational security. To tackle these issues, a model‐based resilient estimation and control framework is proposed, which integrates observer‐based attack detection and fault estimation mechanisms. First, a set of distributed local estimators based on unknown input observers (UIOs) is developed to achieve robust state and fault estimation under disturbances and sparse sensor attacks. Subsequently, a resilient global fusion strategy is established to enhance tolerance against compromised measurements and to ensure bounded estimation errors even in the presence of sensor corruption. Based on the fused estimation results, a resilient fault‐tolerant control scheme is formulated to guarantee closed‐loop stability and desired performance. The proposed framework is applicable to both centralised and distributed smart‐grid configurations. Simulation results on a nonlinear benchmark system demonstrate its effectiveness in detecting cyberattacks, estimating physical faults, and maintaining reliable system operation under adverse conditions.

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Publication Details

Journal
IET Smart Energy Systems
Published
2026-06-13
DOI
https://doi.org/10.1049/ses2.70028
Primary Topic
Smart Grid Security and Resilience
Type
article
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0.00
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article

Cyberattack Detection, Fault Estimation, and Fault‐Tolerant Control of Smart‐Grid Cyber‐Physical Systems

Youmin Zhang, Jin Li
IET Smart Energy Systems
Smart Grid Security and Resilience
article

Cyberattack Detection, Fault Estimation, and Fault‐Tolerant Control of Smart‐Grid Cyber‐Physical Systems

Youmin Zhang, Jin Li
article en

Abstract

ABSTRACT This paper addresses the problem of joint detection and estimation of cyberattacks and physical faults in smart‐grid cyber‐physical systems. In practical smart‐grid environments, physical faults arising from equipment degradation may coexist with malicious cyber threats, leading to significant degradation in system reliability and operational security. To tackle these issues, a model‐based resilient estimation and control framework is proposed, which integrates observer‐based attack detection and fault estimation mechanisms. First, a set of distributed local estimators based on unknown input observers (UIOs) is developed to achieve robust state and fault estimation under disturbances and sparse sensor attacks. Subsequently, a resilient global fusion strategy is established to enhance tolerance against compromised measurements and to ensure bounded estimation errors even in the presence of sensor corruption. Based on the fused estimation results, a resilient fault‐tolerant control scheme is formulated to guarantee closed‐loop stability and desired performance. The proposed framework is applicable to both centralised and distributed smart‐grid configurations. Simulation results on a nonlinear benchmark system demonstrate its effectiveness in detecting cyberattacks, estimating physical faults, and maintaining reliable system operation under adverse conditions.

IET Smart Energy Systems
Concordia University (CA)
Peace, Justice and strong institutions
Openalex Percentile: Top 6%
Smart Grid Security and Resilience
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Cyberattack Detection, Fault Estimation, and Fault‐Tolerant Control of Smart‐Grid Cyber‐Physical Systems — Youmin Zhang, Jin Li · IET Smart Energy Systems (2026) | TGRS Research Map | TGRS