
The authors propose a scalable and efficient partition-based distributed extended Kalman filter method for estimating the states of general nonlinear processes consisting of interconnected subsystems.


coremsg

partition-based-distributed-extended-kalman-filter-for-estimating-large-scale-nonlinear-processes-in-chemical-and-wastewater-treatment-applications


Partition-based Distributed Extended Kalman Filter for Estimating Large-Scale Nonlinear Processes in Chemical and Wastewater Treatment Applications


title_rewrite


The core message of this article is to develop an iterative partition-based distributed moving horizon estimation (DMHE) scheme for linear systems, where the local estimators penalize both system disturbances and measurement noise to provide accurate and stable state estimates.


iterative-distributed-moving-horizon-estimation-for-linear-systems-with-penalties-on-both-system-disturbances-and-noise


Iterative Distributed Moving Horizon Estimation for Linear Systems with Penalties on Both System Disturbances and Noise
