Observer-Based Adaptive Neural Sliding Mode Control of Fuzzy Systems With Sojourn-Probability-Based Multimode Attacks.

Journal: IEEE transactions on cybernetics
Published Date: Apr 1, 2026

Abstract

This article addresses the challenges posed by multimode denial of service (DoS) and deception attacks in observer-based sliding mode control (SMC) for fuzzy nonlinear systems. A novel multimode DoS attack model is introduced, incorporating time-varying sojourn probabilities to provide a more accurate and computationally efficient representation of the stochastic nature of these attacks. This model overcomes the limitations of traditional Markov-based models by capturing dynamic attack behaviors. Deception attacks are modeled as unbounded nonlinear functions, and adaptive neural networks (NNs) are employed to approximate their complex behaviors, significantly reducing their detrimental impact on system stability. A fuzzy sliding surface is designed based on the switching rule for sojourn probabilities, and an observer-based SMC law is proposed to ensure the mean square estimation upper bound of the fuzzy nonlinear systems, guaranteeing stability despite the presence of cyberattacks. Finally, the validity and superiority of the proposed control strategy are demonstrated through a tunnel diode circuit model.

Authors

  • Bin Zhang
    Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Weiling Bao
  • Jun Cheng
    School of Electrical and Information Technology, Yunnan Minzu University, Kunming, Yunnan 650500, PR China. Electronic address: [email protected].
  • Leszek Rutkowski
    * Institute of Computational Intelligence, Czestochowa University of Technology, Al. Armii Krajowej 36, 42-200 Czestochowa, Poland.
  • Dan Zhang
    School of Pharmacy, Southwest Medical University, Luzhou 646000, China.
  • Huaicheng Yan
  • Yuanyuan Shen
    Knowledge Engineering and Discovery Research Institute (KEDRI), School of Engineering Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand.

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