Recursive Minimum-Variance Filter Design for State-Saturated Complex Networks With Uncertain Coupling Strengths Subject to Deception Attacks
Hongyu Gao, Hongli Dong, Zidong Wang, Fei Han
Abstract
In this article, the recursive filtering problem is investigated for state-saturated complex networks (CNs) subject to uncertain coupling strengths (UCSs) and deception attacks. The measurement signals transmitted via the communication network may suffer from deception attacks, which are governed by Bernoulli-distributed random variables. The purpose of the problem under consideration is to design a minimum-variance filter for CNs with deception attacks, state saturations, and UCSs such that upper bounds on the resulting error covariances are guaranteed. Then, the expected filter gains are acquired via minimizing the traces of such upper bounds, and sufficient conditions are established to ensure the exponential mean-square boundedness of the filtering errors. Finally, two simulation examples (including a practical application) are exploited to validate the effectiveness of our designed approach.