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Adaptive Fuzzy Control of Networked Hidden Stochastic Switching Power Systems Under Cyber Attacks.

Wenhai Qi, Mingxuan Sha, Guangdeng Zong

IEEE Transactions on Cybernetics

|May 19, 2025

Summary

This study introduces an adaptive fuzzy asynchronous (AFA) controller for stabilizing discrete networked power systems facing cyber attacks. The AFA controller ensures bounded stability in the mean square, even with asynchronous operation and hidden Markovian switching.

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Area of Science:

Control Systems Engineering
Networked Systems Security
Fuzzy Logic Applications

Background:

Discrete networked systems are vulnerable to cyber attacks, impacting stability.
Asynchronous operation between controllers and systems introduces complexity.
Stochastic semi-Markovian switching adds challenges to system analysis.

Purpose of the Study:

To develop an adaptive fuzzy asynchronous (AFA) stabilization strategy.
To address cyber attacks in discrete networked hidden stochastic semi-Markovian switching power systems.
To ensure bounded stability in the mean square under uncertain conditions.

Main Methods:

Utilizing fuzzy logic rules to model unknown deception cyber attacks.
Employing a hidden semi-Markovian model to characterize asynchronous mechanisms.
Designing an AFA stabilizing controller based on detected modes and fuzzy logic.
Applying a stochastic Lyapunov function for stability analysis.

Main Results:

Sufficient criteria for AFA controller design are established.
Bounded stability in the mean square is guaranteed for the power system.
The proposed scheme demonstrates effectiveness through simulation.

Conclusions:

The developed AFA stabilization scheme effectively manages cyber attacks and asynchronous operations.
The approach ensures robust stability for discrete networked power systems.
This research contributes to secure and reliable control of complex systems.