Distributed filtering based on Cauchy-kernel-based maximum correntropy subject to randomly occurring cyber-attacks

• Published in: Automatica (Oxford) Vol. 135; p. 110004
• Main Authors: Song, Haifang, Ding, Derui, Dong, Hongli, Yi, Xiaojian
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2022
• Subjects: Cyber-attacks; Distributed filtering; Fixed-point iteration; Maximum correntropy; Non-Gaussian noises; Maximum correntropy; Cyber-attacks; Fixed-point iteration; Non-Gaussian noises; Distributed filtering
• ISSN: 0005-1098; 1873-2836
• DOI: 10.1016/j.automatica.2021.110004

This paper is concerned with the distributed filtering issue under the Cauchy-kernel-based maximum correntropy for large-scale systems subject to randomly occurring cyber-attacks in non-Gaussian environments. The considered cyber-attacks are hybrid and consist of both denial-of-service attacks and deception attacks. The weighted Cauchy kernel-based maximum correntropy criterion instead of the traditional minimum variance is put forward to evaluate the filtering performance against non-Gaussian noises as well as cyber-attacks. Based on the matrix decomposition and the fixed-point iterative update rules, the desired filter gain related with a set of Riccati-type equations is obtained to achieve the optimal filtering performance. Then, an improved version only dependent on the local information and neighboring one-step prediction is developed to realize the distributed implementation. Furthermore, the convergence of the developed fixed-point iterative algorithm is addressed via the famous Banach fixed-point theorem. Finally, a standard IEEE 39-bus power system is utilized to show the merit of the proposed distributed filtering algorithm in the presence of cyber-attacks and non-Gaussian noises.