학술논문

Dynamic Event-Triggered Adaptive Neural Network Decentralized Output-Feedback Control for Nonlinear Interconnected Systems With Hybrid Cyber Attacks and Its Application
Document Type
Periodical
Source
IEEE Transactions on Systems, Man, and Cybernetics: Systems IEEE Trans. Syst. Man Cybern, Syst. Systems, Man, and Cybernetics: Systems, IEEE Transactions on. 54(4):2149-2158 Apr, 2024
Subject
Signal Processing and Analysis
Robotics and Control Systems
Power, Energy and Industry Applications
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Cyberattack
Denial-of-service attack
Adaptive control
Vehicle dynamics
Security
Process control
Complexity theory
deception attacks
denial-of-service (DoS) attacks
dynamic event-triggered mechanism
hybrid cyber attacks
nonlinear interconnected systems (NISs)
nonrecursive design
Language
ISSN
2168-2216
2168-2232
Abstract
In this article, a dynamic event-triggered adaptive neural network decentralized nonrecursive output-feedback control scheme for nonlinear interconnected systems under hybrid cyber attacks is first proposed, where the hybrid cyber attacks, containing deception attacks and denial-of-service (DoS) attacks, obey Bernoulli distribution. Taking into account the restrictions imposed by network transmission, a dynamic event-triggered mechanism is introduced to fulfill the analysis and design task. A decentralized linear observer is established to estimate the unknown states. Meanwhile, a decentralized adaptive output-feedback controller is developed in a nonrecursive method with the help of neural network technology. The proposed control scheme can ensure that all signals in the closed-loop system are bounded. Furthermore, Zeno phenomenon can be effectively avoided. Finally, simulation results validate the feasibility of the proposed control scheme.