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<p>This study investigates the problem of adaptive event-triggered asynchronous control (AETAC) for interval type-2 (IT2) fuzzy Markov jump systems (MJS) with uncertain parameters and deception attacks. The objective is to enhance communication efficiency by reducing the frequency of data updates and unnecessary transmissions through the utilization of AETAC. This approach optimally utilizes the limited network resources and mitigates the communication burden. An effective IT2 fuzzy closed loop system is constructed under AETAC to handle deception attacks represented as stochastic distances with uncertainties. The asynchronous behavior between the plant and the controller is characterized using a hidden Markov model (HMM). By employing augmented Lyapunov–Krasovskii functional (LKF) and recently developed integral inequalities, this study establishes sufficient conditions for system analysis in the form of linear matrix inequalities (LMIs). These conditions take into account the existence of zero equations with strictly dissipative performance. Finally, simulation studies on two numerical examples are conducted to demonstrate the effectiveness of the proposed criteria.</p>

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Adaptive event triggering asynchronous control for interval type-2 fuzzy Markov jump systems with uncertainties and deception attacks

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月1日

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  • A. Chandrasekar,
  • Wen-Jer Chang,
  • T. Radhika,
  • S. Santhosh Kumar,
  • Muhammad Shamrooz Aslam

摘要

This study investigates the problem of adaptive event-triggered asynchronous control (AETAC) for interval type-2 (IT2) fuzzy Markov jump systems (MJS) with uncertain parameters and deception attacks. The objective is to enhance communication efficiency by reducing the frequency of data updates and unnecessary transmissions through the utilization of AETAC. This approach optimally utilizes the limited network resources and mitigates the communication burden. An effective IT2 fuzzy closed loop system is constructed under AETAC to handle deception attacks represented as stochastic distances with uncertainties. The asynchronous behavior between the plant and the controller is characterized using a hidden Markov model (HMM). By employing augmented Lyapunov–Krasovskii functional (LKF) and recently developed integral inequalities, this study establishes sufficient conditions for system analysis in the form of linear matrix inequalities (LMIs). These conditions take into account the existence of zero equations with strictly dissipative performance. Finally, simulation studies on two numerical examples are conducted to demonstrate the effectiveness of the proposed criteria.