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Related Experiment Video

Updated: Sep 22, 2025

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

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Published on: February 14, 2025

Formation control for discrete-time multi-agent system with input and output delays under network attacks.

Jian Yuan¹, Hailin Liu², Wenxia Zhang³

¹Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Shandong Provincial Key Laboratory of Ocean Environment Monitoring Technology, National Engineering and Technological Research Center of Marine Monitoring Equipment, Qingdao, China; Key Laboratory of Ocean Observation Technology, MNR, Tianjin, China. yuanjian@qlu.edu.cn.

Scientific Reports

|May 20, 2022

Summary

This study presents a robust consensus control protocol for multi-agent systems (MAS) facing network attacks and delays. It ensures reliable formation control despite disturbances and communication issues.

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Area of Science:

Control Systems Engineering
Robotics
Networked Systems

Background:

Multiple agent systems (MAS) face challenges with input/output delays, network attacks, and noise.
Achieving consensus and formation control in MAS is critical for coordinated tasks.

Purpose of the Study:

To develop a mean square consensus-based formation control protocol for MAS with delays and network attacks.
To address process noise and measurement noise in the multi-agent system.

Main Methods:

A time delay-free transformation approach to convert the system into a delay-free discrete-time system.
A state observer utilizing a Kalman filter for state estimation.
A distributed predictive consensus protocol for leader-following MAS.

Main Results:

Derived sufficient and necessary conditions for mean square consensus under Denial-of-Service (DoS) attacks.
Demonstrated the effectiveness of the proposed protocol through a numerical example.

Conclusions:

The proposed consensus control protocol is effective for MAS with input/output delays and network attacks.
The methodology ensures reliable formation control and mean square consensus in the presence of noise and disturbances.