Cyber-Physical Multi-Agent Systems

This study is based on the hypothesis that an observer-based event-triggered consensus control method can ensure secure and resilient consensus in nonlinear cyber-physical multi-agent systems (CPMASs), even under multiple randomly occurring cyber-attacks such as deception and Denial-of-Service (DoS) attacks.
The dataset used in this research is generated from numerical simulations of a representative CPMAS model, characterized by a directed communication graph and subjected to randomly occurring cyber-attacks. These attacks include both deception and DoS scenarios, designed to emulate realistic and unpredictable network vulnerabilities in cyber-physical infrastructures.
Simulation data include time-series of agent state trajectories, triggering instants, control inputs, and attack indicators. All simulations were carried out in MATLAB/Simulink using the parameters and conditions specified in the manuscript. The data reflect both nominal system behavior and system performance under adversarial conditions.
Notable findings demonstrate that the proposed control framework successfully guarantees resilient consensus and exponential mean-square stability of the CPMASs, even in the presence of multiple attack types. Additionally, the event-triggered mechanism effectively reduces communication frequency between agents, optimizing resource utilization without compromising stability.