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Resilient Consensus Control for Linear Multi-agent System Against the False Data Injection Attacks

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  • Control Theory and Applications
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Abstract

This paper is concerned with the resilient consensus control problem of the linear multi-agent system under the false data injection attacks, where each agent may receive the injected false data by attackers from its neighbours through communication links. Due to the existence of the false data, the desired consensus of multi-agent can not be reached by the general distributed consensus algorithms. By constructing an extended state observer to estimate the state and the injected false data towards each agent, a distributed resilient consensus control algorithm is designed to offset the negative effect of the attacks. Firstly, a sufficient condition is derived for the undirected multi-agent system under a bounded and decaying false data injection. Secondly, a sufficient and necessary condition is provided for the directed multi-agent system under the false data injection with decaying rate. Finally, the simulation results illustrate the effectiveness of the proposed consensus algorithms against the false data attacks.

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Authors and Affiliations

  1. Yonsei Frontier Lab, Yonsei University, Seoul, 03722, Korea

    **de Cao

  2. School of Mathematics, Southeast University, Nan**g, 211189, China

    Meirong Wang, Jianqiang Hu & **de Cao

Authors
  1. Meirong Wang
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  2. Jianqiang Hu
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  3. **de Cao
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Correspondence to Jianqiang Hu.

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Conflict of Interest

The authors declare that there is no conflict of interest with respect to the research, authorship, and/or publication of this paper.

Meirong Wang received her B.S. degree in mathematics and applied mathematics from Fujian Normal University, Fuzhou, China, in 2020. She is currently working toward an M.S. degree with the School of Mathematics, Southeast University, Nan**g, China. Her research interests include false data injection attack and defense methods, and distributed security control of multi-agent systems.

Jianqiang Hu received his B.S. degree in mathematics and applied mathematics from the North China University of Water Resources and Electric Power, Zhengzhou, China, in 2010, and an M.S. degree in applied mathematics from Southeast University, Nan**g, China, in 2013, and his Ph.D. degree in control theory and control engineering, Southeast University, Nan**g, China, in 2016. Currently, he is an associate professor with Jiangsu Provincial Key Laboratory of Networked Collective Intelligence and Department of System Science of School of Mathematics, Southeast University, China. His current research interests include distributed optimization and control of multiagent systems, and demand-side control in smart grids.

**de Cao received his B.S. degree from Anhui Normal University, Wuhu, China, an M.S. degree from Yunnan University, Kunming, China, and a Ph.D. degree from Sichuan University, Chengdu, China, all in mathematics/applied mathematics, in 1986, 1989, and 1998, respectively. He was a Postdoctoral Research Fellow at the Department of Automation and Computer-Aided Engineering, Chinese University of Hong Kong, Hong Kong, from 2001 to 2002. Professor Cao an Endowed Chair Professor, the Dean of the School of Mathematics and the Director of the Research Center for Complex Systems and Network Sciences at Southeast University (SEU). He is also the Director of the National Center for Applied Mathematics at SEU-Jiangsu of China and the Director of the Jiangsu Provincial Key Laboratory of Networked Collective Intelligence of China. Prof. Cao was a recipient of the National Innovation Award of China, Obada Prize and the Highly Cited Researcher Award in Engineering, Computer Science, and Mathematics by Clarivate Analytics. He is elected as a member of Russian Academy of Sciences, a member of the Academy of Europe, a member of Russian Academy of Engineering, a member of the European Academy of Sciences and Arts, a member of the Lithuanian Academy of Sciences, a fellow of African Academy of Sciences, and a fellow of Pakistan Academy of Sciences.

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This work was supported in part by the National Nature Science Foundation of China under Grants 61703095, 61833005, 51807181, 51977032; in part by the Natural Science Foundation of Jiangsu Province of China under Grant BK20170697; in part by the ZhiShan Youth Scholar Program (2242022R40042) from Southeast University.

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Wang, M., Hu, J. & Cao, J. Resilient Consensus Control for Linear Multi-agent System Against the False Data Injection Attacks. Int. J. Control Autom. Syst. 21, 2112–2123 (2023). https://doi.org/10.1007/s12555-022-0261-y

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