Adaptive Neural Security Control for Networked Singular Systems Under Deception Attacks

IEEE Access

Ning Zhao¹  Luis I. Minchala²  Wengang Ao³  Huiyan Zhang³ 

[1] College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, China;Department of Electrical Electronics and Telecommunications Engineering, University of Cuenca, Cuenca, Ecuador;National Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, Chongqing, China;

关键词: Networked singular systems;    neural networks;    security control;    deception attacks;   

DOI  :  10.1109/ACCESS.2022.3161672

来源: DOAJ

【 摘 要 】

This paper studies the issue of the adaptive neural security controller design for uncertain networked singular systems in the presence of deception attacks. Considering that the attack signal is unknown, the neural networks technique is exploited to approximate the attack signal, which eliminates the assumption that the attack signal has a known upper bound. By combining the state feedback with the estimated information of the attack, the impact of the attack is effectively compensated. Furthermore, a novel Lyapunov function, including the decomposed state vector and the weight matrix estimation error, is established to evaluate the bounded area of the system state. Finally, a numerical example substantiates the validity of the theoretical results.

【 授权许可】

Unknown