Secure Tracking Control and Attack Detection for Power Cyber-Physical Systems Based on Integrated Control Decision

In this article, the problems of attack detection and secure tracking control for the power cyber-physical system are investigated. Considering the critical role of cyber networks in influencing decision-making for power grid optimization, a multiobjective optimization problem is introduced to determine the output power of generators. This optimization problem is solved based on the improved particle swarm optimization algorithm. The power system is modelled with dynamic characteristics taken into account. Furthermore, a resilient state-feedback tracking control strategy, that exploits a sliding mode observer, is introduced to ensure the reference value generated by the cyber network is tracked even under attacks. In addition, by using the reconstructed attack signals, an attack detection scheme is proposed. Some sufficient conditions are then obtained for the solvability of the tracking control problem. Finally, a simulation example and the experimental validation built into the StarSim hardware-in-the-loop simulation platform are introduced to illustrate the effectiveness of the proposed method.

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Institutions

Publication Details

Journal
IEEE Transactions on Information Forensics and Security
Published
2024-12-12
DOI
https://doi.org/10.1109/tifs.2024.3516557
Citations
11
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
3.61

Funders

Controls
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article

Secure Tracking Control and Attack Detection for Power Cyber-Physical Systems Based on Integrated Control Decision

Qingyu Su, Chaowei Sun, Jian Li
11 citations
IEEE Transactions on Information Forensics and Security
Smart Grid Security and Resilience
3.61
article

Secure Tracking Control and Attack Detection for Power Cyber-Physical Systems Based on Integrated Control Decision

Qingyu Su, Chaowei Sun, Jian Li
article en
11 citations

Abstract

In this article, the problems of attack detection and secure tracking control for the power cyber-physical system are investigated. Considering the critical role of cyber networks in influencing decision-making for power grid optimization, a multiobjective optimization problem is introduced to determine the output power of generators. This optimization problem is solved based on the improved particle swarm optimization algorithm. The power system is modelled with dynamic characteristics taken into account. Furthermore, a resilient state-feedback tracking control strategy, that exploits a sliding mode observer, is introduced to ensure the reference value generated by the cyber network is tracked even under attacks. In addition, by using the reconstructed attack signals, an attack detection scheme is proposed. Some sufficient conditions are then obtained for the solvability of the tracking control problem. Finally, a simulation example and the experimental validation built into the StarSim hardware-in-the-loop simulation platform are introduced to illustrate the effectiveness of the proposed method.

IEEE Transactions on Information Forensics and SecurityVol. 20
Northeast Electric Power University (CN)
Natural Science Foundation of Jilin Province, Education Department of Jilin Province
Peace, Justice and strong institutions
Openalex Percentile: Top 6%
Smart Grid Security and Resilience
3.61
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