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Securing consensus in fractional-order multi-agent systems: Algebraic approaches against Byzantine attacks
Yubin Zhong1, Asad Khan2, Muhammad Awais Javeed3
1School of Mathematics and Information Science, Guangzhou University, Guangzhou 510006, PR China.
Heliyon
|December 3, 2024
Summary
This study explores fractional-order nonlinear multi-agent systems under Byzantine attacks. We developed algebraic conditions using graph theory and fractional-order Lyapunov methods to ensure leader-following consensus, enhancing system resilience.
Area of Science:
- Control Theory
- Networked Systems
- Nonlinear Dynamics
Background:
- Multi-agent systems (MAS) are crucial for distributed control and coordination.
- Fractional-order systems offer enhanced modeling capabilities but are complex to analyze.
- Byzantine attacks pose significant threats to MAS consensus and integrity.
Purpose of the Study:
- To investigate the consensus behavior of fractional-order nonlinear multi-agent systems under Byzantine attacks.
- To develop robust algebraic conditions for achieving leader-following consensus.
- To enhance the resilience of multi-agent systems against sensor and actuator manipulations.
Main Methods:
- Utilized weighted directed and undirected graphs to represent system topology.
- Combined algebraic graph theory with fractional-order Lyapunov stability techniques.
- Developed novel algebraic requirements for leader-following consensus analysis.
Main Results:
- Presented quantitative results demonstrating the effectiveness of the proposed consensus approach.
- Validated the developed requirements through two numerical examples.
- Showcased the potential of fractional-order systems for improved adversarial resilience.
Conclusions:
- The proposed algebraic framework effectively analyzes consensus in fractional-order nonlinear multi-agent systems under Byzantine attacks.
- Fractional-order dynamics can be leveraged to increase system robustness against adversarial manipulations.
- Findings have implications for secure and reliable distributed control in real-world applications.
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