Learning-Based Model-Free Adaptive Control for Nonlinear Discrete-Time Networked Control Systems Under Hybrid Cyber Attacks

A novel learning-based model-free adaptive control (LMFAC) approach is presented in this article for a class of unknown nonaffine nonlinear discrete-time networked control systems (NCSs) subject to hybrid cyber attacks. The aperiodic denial-of-service (DoS) attacks and persistent deception attacks a...

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Bibliographic Details
Published in:IEEE transactions on cybernetics 2024-03, Vol.54 (3), p.1560-1570
Main Authors: Li, Fanghui, Hou, Zhongsheng
Format: Article
Language:English
Subjects:
Adaptation models
Adaptive control
Attenuation coefficients
Cyberattack
Cybersecurity
Data models
Data-driven control (DDC)
deception attacks
Denial of service attacks
denial-of-service (DoS) attacks
Denial-of-service attack
Discrete time systems
Heuristic algorithms
hybrid cyber attacks
Hybrid systems
Learning
learning-based model-free adaptive control (LMFAC)
Mathematical models
Network control
networked control systems (NCSs)
Nonlinear control
Nonlinear dynamical systems
Security
Tracking errors
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Summary:A novel learning-based model-free adaptive control (LMFAC) approach is presented in this article for a class of unknown nonaffine nonlinear discrete-time networked control systems (NCSs) subject to hybrid cyber attacks. The aperiodic denial-of-service (DoS) attacks and persistent deception attacks are assumed to arise in feedback channels, which could result in the absence or authenticity lackness of system signals sent to the controller. With the aid of dynamic linearizaton technology, the equivalent dynamic linearized data models of considered NCSs are first established only based on I/O information instead of the knowledge of mathematical models that are commonly used under the model-based control framework. Then, an LMFAC scheme is designed on the basis of occurred maximum DoS attacks interval to adaptively tune the attenuation coefficient of the input signal for improving system performance during the next DoS attacks interval. Finally, the boundedness of tracking error is rigorously proved through the contraction mapping principle and the effectiveness of the proposed pure data-driven LMFAC method is demonstrated via simulations.
ISSN:2168-2267
2168-2275
DOI:10.1109/TCYB.2022.3225203