Dynamic Event-Triggered Fusion Filtering for Multi-Sensor Rectangular Descriptor Systems With Random State Delay

Abstract

This paper investigates the dynamic event-triggered fusion filtering problem for a class of uncertain multi-sensor rectangular descriptor systems with random state delay. The random state delay is depicted by a Bernoulli distributed random variable. In order to save the communication energy, a dynamic event-triggered mechanism (DETM) is employed to decide whether the measurements are transmitted to the local estimators. Firstly, by introducing the full-order transformation method, the rectangular descriptor systems are converted into the non-descriptor systems with full orders. Secondly, the local filter gains are designed to minimize the upper bounds of filtering error covariances (FECs), where the upper bounds of FECs and the filter gains depend on a group of free positive scalar parameters. To minimize the upper bounds of FECs, the scalar parameters are sought optimally by a numerical method, where the scalars obtained after optimization are called optimal parameters. Subsequently, the fusion filter of the original descriptor system is given by the inverse covariance intersection (ICI) fusion technique. Finally, the effectiveness and advantages of the proposed fusion filtering algorithm are illustrated by providing the experiments with circuit system application.