Anti-Attack Secure Fuzzy Adaptive Control for NMASs With Switching-Type Secure Estimator.

Area of Science:

• Control Systems Engineering
• Artificial Intelligence
• Cybersecurity

Background:

• Nonlinear multiagent systems (NMASs) are susceptible to denial-of-service (DoS) attacks.
• Unobservable system states complicate control and monitoring during attacks.
• Fuzzy logic systems (FLSs) offer a framework for modeling complex nonlinear dynamics.

Purpose of the Study:

• To develop a secure output-feedback control strategy for NMASs under DoS attacks with unobservable states.
• To design a switching-type secure estimator for reconstructing system states from limited data.
• To ensure system stability and consensus tracking despite security threats.

Main Methods:

• Fuzzy logic systems (FLSs) for modeling nonlinear dynamics.
• A switching-type secure estimator to reconstruct states from sporadic outputs.
• Average dwell time (ADT) method and Lyapunov stability theory for control design.

Main Results:

• The proposed secure control strategy maintains system stability under DoS attacks.
• Consensus tracking errors converge even with unknown states and intermittent data.
• Simulation experiments validate the effectiveness and reliability of the control scheme.

Conclusions:

• The developed output-feedback secure control strategy effectively addresses DoS attacks in NMASs with unobservable states.
• The switching estimator successfully reconstructs system states, enabling continuous monitoring and control.
• The integration of ADT and Lyapunov stability guarantees robust system performance.