Memory Fusion Sampled-Data Control of Fractional-Order Heterogeneous Multiagent Systems Subject to DoS Attacks and...

Area of Science:

• Control Systems Engineering
• Networked Systems
• Fractional Calculus

Background:

• Fractional-order (FO) multiagent systems (MASs) are increasingly complex, requiring robust control strategies.
• Nonidentical denial-of-service (DoS) attacks and time delays pose significant challenges to the stability and performance of MASs.
• Traditional periodic sampling methods are often insufficient for heterogeneous systems under dynamic attack scenarios.

Purpose of the Study:

• To investigate and develop a channel-dependent resilient binary sampled-data control scheme for heterogeneous FO MASs.
• To address the challenges posed by nonidentical DoS attacks and time delays in sampled-data control systems.
• To enhance the connectivity and consensus performance of FO MASs under asynchronous DoS attacks.

Main Methods:

• A channel-dependent resilient binary sampled-data scheme that adjusts sampling periods based on acknowledgments and two geometric progressions.
• Analysis of sampling intervals with heterogeneous upper and lower bounds, constrained by DoS attack coefficients.
• Utilizing heterogeneous memory fusion controllers and a distributed asynchronous gradient algorithm for consensus.
• Defining and observing joint recovery time series to measure network topology restoration under DoS attacks.

Main Results:

• The designed scheme achieves finer adjustments in sampling periods, leading to a lower average sampling rate than traditional methods.
• The effectiveness of the sampling scheme in restoring communication network connectivity under DoS attacks is demonstrated.
• Consensus in heterogeneous FO MASs with time delays is achieved using the proposed control strategy.
• Theoretical analysis is validated through a presented illustrative example.

Conclusions:

• The developed sampled-data control scheme effectively manages heterogeneous FO MASs under DoS attacks and time delays.
• The adaptive sampling strategy enhances system resilience and network connectivity restoration.
• The findings contribute to the advancement of robust control techniques for complex networked systems.