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Event-Triggered State Estimation for T–S Fuzzy Neural Networks with Stochastic Cyber-Attacks

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Abstract

This paper is mainly concerned with event-triggered state estimation for Takagi–Sugeno (T–S) fuzzy neural networks subjected to stochastic cyber-attacks. An event-triggered scheme is utilized to decide whether the sampled data should be delivered or not. By taking the influence of the cyber-attacks into consideration, a T–S fuzzy model for the state estimation of neural networks is established with the event-triggered scheme. Through the utilization of Lyapunov stability theory and linear matrix inequality (LMI) techniques, the sufficient conditions are derived which can ensure the stability of estimator error systems. In addition, the gains of the estimator are acquired in the form of LMIs. Finally, a simulated example is presented to illustrate the effectiveness of the proposed method.

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Author information

Authors and Affiliations

  1. College of Information Engineering, Nanjing University of Finance and Economics, Nanjing, 210023, China

    Jinliang Liu & Tingting Yin

  2. Key Laboratory of Grain Information Processing and Control, Henan University of Technology, Ministry of Education, Henan, 450001, China

    Jinliang Liu

  3. Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210023, Jiangsu, China

    Xiangpeng Xie

  4. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Engang Tian

  5. School of Automation, Southeast University, Nanjing, 210096, Jiangsu, China

    Shumin Fei

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  1. Jinliang Liu
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  2. Tingting Yin
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  3. Xiangpeng Xie
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  4. Engang Tian
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  5. Shumin Fei
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Corresponding author

Correspondence to Jinliang Liu.

Additional information

This work was supported in part by the Open Fund of Key Laboratory of Grain Information Processing and Control of Hennan Province of China under Grant KFJJ-2018-203, and in part by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China under Grant 18KJB120002, and in part by the Natural Science Foundation of Jiangsu Province of China under Grant BK20171481, and in part by National Key Research and Development Program of China (Project Nos. 2017YFD0401001, 2018YFD0401404), and in part by the Key Research and Development Program of Jiangsu Province (Project No. BE2016178).

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Liu, J., Yin, T., Xie, X. et al. Event-Triggered State Estimation for T–S Fuzzy Neural Networks with Stochastic Cyber-Attacks. Int. J. Fuzzy Syst. 21, 532–544 (2019). https://doi.org/10.1007/s40815-018-0590-4

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  • DOI: https://doi.org/10.1007/s40815-018-0590-4

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