Distributed Multi-objective Estimation for Continuous Systems with Sensor Networks

This paper is concerned with the problem of distributed multi-objective filters (DMFs) design for a class of linear time-invariant (LTI) continuous-time systems with sensor networks (SNs). According to the topology of the SN, a set of distributed filters are given as Luenberger-like with consensus terms in order to estimate the state in a fully distributed manner. Then, a less conservative sufficient condition is proposed in terms of linear matrix inequalities (LMIs) to such that the filtering error systems of all local DMFs are stable with an H. performance constraint and a quadratic cost function is minimized in the absence of external disturbances. Moreover, a suboptimal distributed filter design is also proposed. Finally, a simulation example is used to demonstrate the effectiveness and merit of the proposed DMFs design scheme.