  In this paper, we consider distributed simultaneous state and parameter
estimation for a class of nonlinear systems, for which the augmented model
comprising both the states and the parameters is only partially observable.
Specifically, we first illustrate how the sensitivity analysis (SA) can select
variables for simultaneous state and parameter estimation. Then, a community
structure detection (CSD) based process decomposition method is proposed for
dividing the entire system into interconnected subsystems as the basis of
distributed estimation. Next, we develop local moving horizon estimators based
on the configured subsystem models, and the local estimators communicate with
each other to exchange their estimates. Finally, an SA and CSD based
distributed moving horizon estimation (DMHE) mechanism is proposed. The
effectiveness of the proposed approach is illustrated using a chemical process
consisting of four connected reactors.
