[HTML][HTML] Review and classification of recent observers applied in chemical process systems
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 …
due to the lack of appropriate estimating devices or to replace high-priced sensors in a plant …
Artificial Intelligence techniques applied as estimator in chemical process systems–A literature survey
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 …
modelling and control only, but also as estimators to estimate the unmeasured parameters …
Development and application of machine learning‐based prediction model for distillation column
Distillation is an energy‐consuming process in the chemical industry. Optimizing operating
conditions can reduce the amount of energy consumed and improve the efficiency of …
conditions can reduce the amount of energy consumed and improve the efficiency of …
ANN-based estimator for distillation using Levenberg–Marquardt approach
In modern chemical industries the purity of the distillate is the main objective and time to
estimate the distillate composition is also the constraint. In the present paper, the Levenberg …
estimate the distillate composition is also the constraint. In the present paper, the Levenberg …
Adaptive system identification of industrial ethylene splitter: A comparison of subspace identification and artificial neural networks
M Jalanko, Y Sanchez, V Mahalec… - Computers & Chemical …, 2021 - Elsevier
The manuscript considers the problem of data-driven modeling of an ethylene splitter (from
an industrial plant). The process presently operates with end composition controllers that …
an industrial plant). The process presently operates with end composition controllers that …
Heat exchanger fouling model and preventive maintenance scheduling tool
The crude preheat train (CPT) in a petroleum refinery consists of a set of large heat
exchangers which recovers the waste heat from product streams to preheat the crude oil. In …
exchangers which recovers the waste heat from product streams to preheat the crude oil. In …
White-box Machine learning approaches to identify governing equations for overall dynamics of manufacturing systems: A case study on distillation column
Dynamical equations form the basis of design for manufacturing processes and control
systems; however, identifying governing equations using a mechanistic approach is tedious …
systems; however, identifying governing equations using a mechanistic approach is tedious …
Soft sensor based composition estimation and controller design for an ideal reactive distillation column
In this research work, the authors have presented the design and implementation of a
recurrent neural network (RNN) based inferential state estimation scheme for an ideal …
recurrent neural network (RNN) based inferential state estimation scheme for an ideal …
New distributed-action control strategy with simultaneous heating and cooling in trays of a pilot-scale diabatic distillation column
In order to minimize operation transient times, a new distributed control strategy was
performed in a distillation unit. Acting simultaneously by heating in tray 11 (strip** …
performed in a distillation unit. Acting simultaneously by heating in tray 11 (strip** …
Neuro-fuzzy soft sensor estimator for benzene toluene distillation column
EA Jalee, K Aparna - Procedia Technology, 2016 - Elsevier
The distillation is widely used separation technique in oil and gas refineries. Accurate
measurement of the composition of separated constituents is necessary to estimate the …
measurement of the composition of separated constituents is necessary to estimate the …