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.