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Adaptive event-triggered state estimation for large-scale systems subject to deception attacks

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Abstract

This paper addresses state estimation issues of large-scale systems with measurements subject to deception attacks, where the communication topology among sub-estimators is the same as the physical coupling structure of the subsystems. In consideration of the limited channel bandwidth, a novel adaptive event-triggered scheme is proposed for governing the data transmission among sub-estimators. With the help of Lyapunov analysis approaches, sufficient conditions are derived to ensure the input-to-state stability of the dynamics of estimation errors. Meanwhile, the bound of the estimation errors is obtained in the mean-square sense. The desired estimator parameters are presented in an analytical form dependent on the solution of a set of matrix inequalities. The developed scheme is related to the local information of the subsystems and thus satisfies the requirement of scalability. Finally, a simulation example of power systems is given to reveal the usefulness and effectiveness of the developed design scheme.

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61973219, 61933007, 61873058) and Natural Science Foundation of Shanghai (Grant No. 18ZR1427000).

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Authors and Affiliations

  1. College of Science, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Hanchen Xiao & Guoliang Wei

  2. Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Derui Ding

  3. School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, VIC, 3122, Australia

    Derui Ding

  4. Institute of Complex Systems and Advanced Control, Northeast Petroleum University, Daqing, 163318, China

    Hongli Dong

Authors
  1. Hanchen Xiao
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  2. Derui Ding
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  3. Hongli Dong
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  4. Guoliang Wei
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Correspondence to Derui Ding.

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Xiao, H., Ding, D., Dong, H. et al. Adaptive event-triggered state estimation for large-scale systems subject to deception attacks. Sci. China Inf. Sci. 65, 122207 (2022). https://doi.org/10.1007/s11432-020-3142-5

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  • DOI: https://doi.org/10.1007/s11432-020-3142-5

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