Observers are computational algorithms designed to estimate unmeasured state variables
due to the lack of appropriate estimating devices or to replace high-priced sensors in a plant …

Abstract The versatility of Artificial Intelligence (AI) in process systems is not restricted to
modelling and control only, but also as estimators to estimate the unmeasured parameters …

The progressive deterioration of water resources and the large amount of polluted water
generated in industrialized societies gives Wastewater Treatment (WWT) processes a …

An estimation approach to jointly design the estimation model, data assimilation structure,
and algorithm in the light of particular estimation objectives is developed within a …

This work investigates the design of alternative monitoring tools based on state estimators
for industrial crystallization systems with nucleation, growth, and agglomeration kinetics. The …

Traditionally, soft sensors are developed based on measurement data only, but here we
consider an adaptive soft sensor that uses data generated from a fitted, first principles model …

We focus on the output tracking problem of distributed parameter systems (DPSs) which can
be described by a set of nonlinear dissipative partial differential equations (PDEs). The …

The problem of designing the state estimation structure for staged process is addressed
within a geometric estimation (GE) framework, with the class of binary columns as case …

In this work, a geometric observer (GO) is formulated and tested using experimental data
from the Automatic Continuous Online Monitoring of Polymerization reactions (ACOMP) …

The aim of this study is to provide a full comprehensive study of the singular linear
parameter‐varying (LPV) systems and observer synthesis in a real process. The states and …