Dynamic Event-Triggered Approach for Distributed State and Parameter Estimation Over Networks Subjected to Deception Attacks

被引:35
作者
Basit, Abdul [1 ]
Tufail, Muhammad [1 ]
Rehan, Muhammad [1 ]
Ahn, Choon Ki [2 ]
机构
[1] Pakistan Inst Engn & Appl Sci PIEAS, Dept Elect Engn, Islamabad 45650, Pakistan
[2] Korea Univ, Sch Elect Engn, Seoul 136701, South Korea
来源
IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS | 2023年 / 9卷
基金
新加坡国家研究基金会;
关键词
Wireless sensor networks; event-triggered; deception attacks; state estimation; unknown parameter; SENSOR NETWORKS; SYSTEMS;
D O I
10.1109/TSIPN.2023.3277278
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This study is focused on addressing the dynamic event-triggered distributed state and unknown parameter estimation problem for discrete-time nonlinear systems that have known linear dynamics and unknown nonlinearities and are subject to deception attacks. A neural-network-based unified estimation framework is introduced to estimate the unknown nonlinear function in conjunction with the system state and unknown parameters. Each sensor uses its own measurements and data from the neighboring sensors to calculate the overall estimates. The information-sharing network is assumed to be vulnerable to deception attacks, which are modeled using a Bernoulli distributed random variable. Additionally, a dynamic event-triggered strategy is adopted to alleviate resource consumption. Based on Lyapunov theory, the stability of the unified estimation framework is proven in terms of the uniformly ultimately bounded error. Moreover, the design conditions for the estimator are presented in the form of matrix inequalities. Finally, a simulation example is presented to demonstrate the effectiveness of the proposed framework.
引用
收藏
页码:373 / 385
页数:13
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