Networked state estimation over a shared communication medium

This paper considers state estimation for multiple plants across a shared communication network. Each linear time-invariant plant transmits information through the common network according to either a time-triggered or an event-triggered rule. Performance in terms of the communication frequency and the estimation error covariance is analytically characterized. The main result is that for the same average communication rate, event-triggered schemes may perform worse than time-triggered schemes in terms of the resulting estimation error covariance when the effect of communication network is explicitly considered.