Event-triggered set-membership fusion estimation of multi-rate multi-sensor systems under multiple cyber attacks

Abstract

The article concerns the multi-rate multi-sensor systems set-membership fusion estimation problem under multiple cyber attacks. In order to save limited communication resources, a novel adaptive event-triggered strategy is developed to control the frequency of information transmission. In contrast to conventional adaptive strategies, a transformation law is introduced to establish the triggering condition, thereby effectively avoiding triggering behaviors caused by small fluctuations after the error has converged. In addition, a hybrid approach is proposed to address the issue of rate inconsistency among various components, significantly improving both the efficiency and accuracy of the estimation algorithm. Then, a cryptography-based privacy protection scheme is presented to defend against deception attacks and replay attacks. By incorporating the concept of set-membership estimation, an optimization problem for secure fusion estimation is formulated. In light of this, an online recursive algorithm is proposed to continuously obtain the weighting coefficients and the optimal ellipsoid set, ensuring that the error remains confined within the desired ellipsoid. Finally, the superiority and feasibility of the proposed scheme are validated through a simulation example and a practical experiment.