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<p>This work focuses on the adaptive event-triggered control problem for complex dynamical networks vulnerable to deception attacks, time-varying coupling delays, and actuator failure. It is assumed that actuator failure and deception attacks occur during data transmission over the network and are modelled by a stochastic variable with a Bernoulli distribution. The adaptive event-triggered strategy is presented to maximize network bandwidth usage and can be adjusted adaptively based on the circumstances. The adaptive event-triggered control (AETC) was designed to reduce the effects of actuator failure and deception attacks on the system’s functionality. Furthermore, sufficient conditions are derived by applying the Lyapunov functional, and a co-design strategy for control gain and event-triggering parameters is obtained. Lastly, two examples are provided to illustrate the effectiveness and advantages of the proposed approach.</p>

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\(H_{\infty }\) Secure Control for Complex Dynamical Networks with Actuator Failure Under Attacks via Adaptive Event-Triggered Mechanism

  • 期刊论文

  • 发表日期：

    2025年3月13日

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  • M. Mubeen Tajudeen,
  • K. Asmiya Banu,
  • Grienggrai Rajchakit,
  • T. Aparna,
  • Oh Min Kwon,
  • Jinde Cao,
  • Anuwat Jirawattanapanit

摘要

This work focuses on the adaptive event-triggered control problem for complex dynamical networks vulnerable to deception attacks, time-varying coupling delays, and actuator failure. It is assumed that actuator failure and deception attacks occur during data transmission over the network and are modelled by a stochastic variable with a Bernoulli distribution. The adaptive event-triggered strategy is presented to maximize network bandwidth usage and can be adjusted adaptively based on the circumstances. The adaptive event-triggered control (AETC) was designed to reduce the effects of actuator failure and deception attacks on the system’s functionality. Furthermore, sufficient conditions are derived by applying the Lyapunov functional, and a co-design strategy for control gain and event-triggering parameters is obtained. Lastly, two examples are provided to illustrate the effectiveness and advantages of the proposed approach.