Cyber-physical system parameter-unknown intrusion control method and device under malicious attack

By designing a fixed-time neural adaptive controller, the control problem of nonlinear cyber-physical systems with unknown parameters under malicious attacks is solved. The system state error is converged within a fixed time, reducing the accuracy requirements of the system model and making it suitable for the security control of various cyber-physical systems.

CN117792773BActive Publication Date: 2026-07-24UNIV OF SCI & TECH BEIJING
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
UNIV OF SCI & TECH BEIJING
Filing Date
2023-12-29
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Existing technologies cannot effectively solve the fixed-time control problem of nonlinear cyber-physical systems with unknown parameters under malicious attacks, cannot meet the system convergence time requirements, and have high requirements for system models and attack perception, and cannot handle the stability of systems whose initial states exceed the limits.

Method used

A virtual controller is designed using the mathematical model of a high-order nonlinear cyber-physical system, error transfer function, coordinate transformation, backstepping method, and obstacle Lyapunov method. By combining Gaussian radial basis function neural network and parameter adaptive method, unknown nonlinear terms and malicious attacks are fitted to design a fixed-time neural adaptive controller.

Benefits of technology

It achieves system state error convergence within a fixed time for high-order nonlinear cyber-physical systems with unknown parameters under malicious attacks, reduces the accuracy requirements of the system model, and can handle error convergence under arbitrary initial states, making it suitable for security control of various cyber-physical systems.

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Abstract

The present application relates to the field of security, in particular to a parameter-unknown information physical system intrusion tolerance control method and device under malicious attack, the method comprises the following steps: according to the structure of high-order nonlinear information physical system, the restriction condition of state variable and the form of malicious attack, the mathematical model of high-order nonlinear information physical system under parameter-unknown malicious attack is established, according to mathematical model, error transfer function and coordinate transformation, the error mathematical model of high-order nonlinear information physical system is established;According to the error mathematical model, the backstepping method and the obstacle lyapunov method, a virtual controller is designed;According to the gaussian radial basis function neural network and the parameter adaptive method, the unknown nonlinear term in the high-order nonlinear information physical system and the malicious attack are fitted, and the fitting result is obtained;Based on the fixed time convergence criterion, the virtual controller and the fitting result, a fixed time neural adaptive controller is designed, and the intrusion tolerance control of the nonlinear information physical system is realized.
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