Distributed fuzzy filtering for load frequency control of non‐linear interconnected power systems under cyber‐physical attacks

Hu, Zhijian; Liu, Shichao; Yang, Liu; Wu, Ligang

doi:10.1049/iet-cta.2019.0268

Cited by 17 publications

(9 citation statements)

References 41 publications

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“…Given that approximate membership function is difficult to perfectly capture all the information of upper and lower bound MFs, and the computational complexity will increase with the increase of approximation degree, how to capture more information of MFs with reasonable computational demand is a point to be explored in this paper. Some notable related practical applications of IT2 fuzzy models in various types of systems are shown in [30]- [34], which will enlighten the theoretical applications studied in this paper. Among them, [30]- [32] explored the implement of IT2 fuzzy model in mobile robots systems.…”

Section: Introductionmentioning

confidence: 94%

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ℓ₂–ℓ∞ Control of Discrete-Time State-Delay Interval Type-2 Fuzzy Systems via Dynamic Output Feedback

Zeng

Lam

Xiao

et al. 2022

IEEE Trans. Cybern.

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Section: Introductionmentioning

confidence: 94%

“…[33] improved the control performance of the generator-based wind turbines by using IT2 fuzzy model. [34] implemented the IT2 fuzzy framework to the control problem of power system.…”

Section: Introductionmentioning

confidence: 99%

ℓ₂–ℓ∞ Control of Discrete-Time State-Delay Interval Type-2 Fuzzy Systems via Dynamic Output Feedback

Zeng

Lam

Xiao

et al. 2022

IEEE Trans. Cybern.

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“…With the rapid development of networking, computing, intelligence and modern control, cyber‐physical systems (CPSs) have generated considerable research interest in the past few years. CPSs deeply integrate information systems with physical systems, and have a wide range of applications in smart grids, 1,2 industrial manufacture, 3 aerospace, 4 and intelligent transportation 5 . However, due to the use of wireless networks, CPSs are vulnerable to cyber‐attacks 6‐8 …”

Section: Introductionmentioning

confidence: 99%

Optimal filter design for cyber‐physical systems under stealthy hybrid attacks

Lin

Lam

2020

Intl J Robust & Nonlinear

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This article studies the optimal filtering problem for cyber‐physical systems under stealthy hybrid cyber‐attacks. Due to the stealthiness of cyber‐attacks, the optimal filter (OF) consists of an exponentially increasing number of terms, which makes it computationally infeasible in practice. To address this computational issue, an optimal linear filter (OLF) is developed with its estimation performance fairly close to the optimal one. Furthermore, for a system under the stealthy hybrid cyber‐attacks, it is proved that when the system is stable, the exponentially increasing number of terms remain bounded, making the OF stable; and that the OLF is stable if and only if the system is stable. Finally, numerical examples are employed to illustrate the effectiveness of the proposed two filters.

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“…In recent years, cyber‐physical systems (CPSs) have experienced significant growth in a wide range of applications including electrical distribution grids, oil and natural gas networks, transportation systems etc. [1, 2]. In the CPSs, there exists a large number of communication links, which makes such systems susceptible to cyber‐attacks targeting the control and sensing modules.…”

Section: Introductionmentioning

confidence: 99%

Efficient resilient dynamic co‐estimation framework for cyber‐physical systems under sensor attacks

Kazemi

Safavi

Setoodeh

2020

IET Control Theory & Appl

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In this study, a novel co‐estimation approach is proposed for dynamic state estimation of cyber‐physical systems (CPSs) subjected to sensor attacks. In the proposed approach, the sensory measurements are preprocessed to extract some valuable information about the launched cyber‐attack. This information is then manipulated to form new state equations, which are augmented with the CPS model. The newly obtained model effectively represents the behaviour of both the CPS states as well as the launched cyber‐attack, and can be used for their co‐estimation. Two structures are suggested for the preprocessing of the sensory measurements that deploy Kalman filter (KF) and two‐step KF for co‐estimation of the states and cyber‐attacks. To effectively handle the concurrent effects of cyber‐attacks and unknown inputs on the CPS co‐estimation process, some auxiliary outputs are generated using high‐gain approximate differentiators to realise the required matching conditions. The proposed dynamic co‐estimation approach improves accuracy via considering the inter‐correlation between the CPS states and the cyber‐attacks. To demonstrate the viability of the proposed co‐estimation method, thorough stability and feasibility analysis are provided. Furthermore, extensive simulations are performed on a well‐known CPS‐the IEEE 14‐bus test system‐ to demonstrate the effectiveness of the proposed approach.

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Distributed fuzzy filtering for load frequency control of non‐linear interconnected power systems under cyber‐physical attacks

Cited by 17 publications

References 41 publications

ℓ₂–ℓ∞ Control of Discrete-Time State-Delay Interval Type-2 Fuzzy Systems via Dynamic Output Feedback

ℓ₂–ℓ∞ Control of Discrete-Time State-Delay Interval Type-2 Fuzzy Systems via Dynamic Output Feedback

Optimal filter design for cyber‐physical systems under stealthy hybrid attacks

Efficient resilient dynamic co‐estimation framework for cyber‐physical systems under sensor attacks

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