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Event-triggered robust distributed output feedback model predictive control for nonlinear MASs against false data

Zhengcai Li¹, Huiling Xu¹, Zhiping Lin²

¹School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing, 210094, China.

ISA Transactions

|July 22, 2023

Summary

This summary is machine-generated.

This study proposes an event-triggered control for nonlinear multiagent systems facing cyber attacks. It ensures system stability and security by separating true states from false data injections.

Keywords:

Distributed output feedback model predictive control Event-triggered mechanism False data injection attacks Robust multivariate observer

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Area of Science:

Control Systems Engineering
Cybersecurity
Robotics

Background:

Multiagent systems are vulnerable to cyber attacks, specifically false data injection.
Maintaining system stability and security in disturbed nonlinear multiagent systems is challenging.

Purpose of the Study:

To develop an event-triggered distributed output feedback model predictive control (MPC) scheme.
To address cyber attacks in nonlinear disturbed multiagent systems.

Main Methods:

A robust multivariate observer estimates system states, false data, and disturbances.
A distributed predictive controller with a linear robustness constraint ensures cooperative stabilization.
An event-triggered mechanism optimizes resource usage and guarantees control problem feasibility.

Main Results:

The proposed scheme effectively separates uncompromised states from false data injection attacks and disturbances.
Smooth cooperative stabilization of nonlinear multiagent systems is achieved.
Theoretical analyses confirm the robustness and security of the proposed control strategy.

Conclusions:

The event-triggered distributed MPC scheme enhances the security and stability of nonlinear multiagent systems against cyber attacks.
The developed observer and control strategy provide a robust solution for real-world applications.