The DOI matches its Crossref record.
Memory-Based Event-Triggering H∞Load Frequency Control for Power Systems Under Deception Attacks
Abstract
This article proposes a memory-based eventtriggering H∞load frequency control (LFC) method for power systems through a bandwidth-constrained open network. To overcome the bandwidth constraint, a memory-based event-triggered scheme (METS) is first proposed to reduce the number of transmitted packets. Compared with the existing memoryless event-triggered schemes, the proposed METS has the advantage to utilize series of the latest released signals. To deal with the random deception attacks induced by open networks, a networked power system model is well established, which couples the effects of METS and random deception attacks in a unified framework. Then, a sufficient stabilization criterion is derived to obtain the memory H∞LFC controller gains and event-triggered parameters simultaneously. Compared with existing memoryless LFC, the control performance is greatly improved since the latest released dynamic information is well utilized. Finally, an illustrative example is used to show the effectiveness of the proposed method.
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Citations
Cited by
Secure Frequency Control of Hybrid Power System Under DoS Attacks via Lie Algebra
Cheng, Z., Yue, D., Shen, S., Hu, S., & Chen, L. (2022) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2022.3158550 · Cited by 54
A novel semantic-based multi-packet parallel transmission scheme for networked control systems
Yang, H., Peng, C., Cao, Z., & Zhang, X.-M. (2025) · Automatica · doi:10.1016/j.automatica.2025.112120 · Cited by 44
Self-citation
Metadata
- Authors
- Tian, E., & Peng, C.
- Venue
- IEEE Transactions on Cybernetics
- Published
- 2020-11
- Volume
- 50
- Issue
- 11
- Pages
- 4610-4618
- ISSN
- 2168-2267 (ISSN-L)
- 2168-2275
- OpenAlex
- W3011490591
- Cited by
- 549
- References
- 0
- FWCI
- 26.25
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
