Journal of Guangxi Normal University(Natural Science Edition) ›› 2026, Vol. 44 ›› Issue (5): 122-134.doi: 10.16088/j.issn.1001-6600.2025111901

• Mathematics and Statistics • Previous Articles     Next Articles

Dynamic quantization control for T-Sfuzzy NCSs under hybrid attacks

Liang Caihong1,2, Wang Hailing1,2*   

  1. 1. School of Mathematics and Statistics, Guangxi Normal University, Guilin Guangxi 541006, China;
    2. The Center for Applied Mathematics of Guangxi (Guangxi Normal University), Guilin Guangxi 541006, China
  • Received:2025-11-19 Revised:2025-12-26 Online:2026-09-05 Published:2026-07-24

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Abstract: A control strategy integrating dynamic quantization and an improved memory event-triggered mechanism is proposed for T-S fuzzy systems subject to limited network bandwidth. Firstly, in order to decrease the burden of network transmission, a dynamic quantizer is introduced to process system states. Secondly, a memory event-triggered mechanism incorporating historically transmitted data is designed to further minimize unnecessary data transmissions. Taking into account that aperiodic denial-of-service (DoS) attacks and deception attacks may occur during network communication, a hybrid attack model is established, with explicit conditions on the maximum allowable attack frequency and duration derived. A controller making full use of historical information is designed, in which the controller gain matrices and the weight matrices of the event-triggering condition are obtained using linear matrix inequality (LMI) techniques, thereby achieving co-optimization of controller gains with quantization parameters, triggering thresholds, and attack characteristics. Subsequently, a Lyapunov-Krasovskii functional is constructed, and sufficient conditions are derived to ensure the asymptotic stability of the closed-loop system while satisfying the prescribed H∞ performance. Lastly, a numerical example is provided to illustrate the effectiveness of the proposed control strategy.

Key words: dynamic quantization, improved memory event-triggered mechanism (IMETM), DoS attacks, deception attacks, T-S fuzzy systems

CLC Number:  TP13
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