General event-triggered dynamic output feedback control for complex networks subject to cyber attacks.

Area of Science:

• Control Systems Engineering
• Network Security
• Dynamical Systems Theory

Background:

• Complex dynamical networks are vulnerable to cyberattacks, impacting system stability.
• Event-triggered control strategies aim to reduce communication load.
• Markovian jump systems introduce stochasticity and mode-dependent dynamics.

Purpose of the Study:

• To develop an adaptive event-triggered dynamic output feedback control for Markovian jump complex dynamical networks (MJCNDs) under cyberattacks.
• To propose a novel adaptive event-triggered mechanism (AETM) with enhanced flexibility.
• To achieve finite-time synchronization for the closed-loop system.

Main Methods:

• A new adaptive event-triggered mechanism (AETM) with dynamic parameter adjustment and mode-dependent properties.
• Construction of a unified dynamic output feedback model integrating unmeasurable states, cyberattacks, event-triggering, and time delays.
• Derivation of sufficient conditions for finite-time synchronization using Lyapunov stability theory and relevant analysis techniques.

Main Results:

• The proposed AETM effectively reduces communication frequency while maintaining control performance.
• The unified dynamic output feedback model demonstrates robustness against cyberattacks and time delays.
• Sufficient conditions guaranteeing finite-time synchronization of the MJCNDs were successfully derived.

Conclusions:

• The developed event-triggered control strategy is effective for securing MJCNDs against cyberattacks.
• The proposed approach offers improved flexibility and communication efficiency compared to existing methods.
• Simulation results validate the effectiveness and superiority of the proposed control scheme.