Self-Triggered Consensus Filtering over Asynchronous Communication Sensor Networks

Abstract

In this paper, a self-triggered consensus filtering is developed for a class of discrete-time distributed filtering systems. Different from existing event-triggered filtering, the self-triggered one does not require to continuously judge the trigger condition at each sampling instant and can save computational burden while achieving good state estimation. The triggering policy is presented for pre-computing the next execution time for measurements according to the filter’s own data and the latest released data of its neighbors at the current time. However, a challenging problem is that data will be asynchronously transmitted within the filtering network because each node self-triggers independently. Therefore, a co-design of the self-triggered policy and asynchronous distributed filter is developed to ensure consensus of the state estimates. Finally, a numerical example is given to illustrate the effectiveness of the consensus filtering approach.