Nonlinear state estimation is a useful approach to the monitoring of industrial (polymerization) processes. This paper investigates how this approach can be followed to the development of a soft sensor of the product quality (melt index). The bottleneck of the successful application of advanced state estimation algorithms is the identification of models that can accurately describe the process
Abstract – Soft sensors are used widely to estimate a process variable which is difficult to measure...
International audienceAdaptive and high gain nonlinear observers are used for state and parameter es...
We propose a soft sensing method using local partial least squares models with adaptive process stat...
Nonlinear state estimation is a useful approach to the monitoring of industrial (polymerization) pr...
Online measurement of the melt index is typically unavailable in industrial polypropyleneproductionp...
An empirical model has been developed for the successful prediction of the melt index (MI) during gr...
Polymerization processes are important industrial processes where the polymer product can be made in...
Abstract: Since the online measurement of melt index (MI) of polyethylene is difficult, a virtual se...
A nonlinear reduced-order state observer is applied to estimate the degree of polymerization in a se...
State estimators, including observers and Bayesian filters, are a class of model-based algorithms fo...
This paper considers the development of multivariate statistical soft sensors for the online estimat...
In chemical processes, online measurements of all the process variables and parameters required for ...
This paper concerns nun-linear state estimation in a batch polymerization reactor where suspension p...
A moving-horizon inferential-state estimation technique is described which uses simulated "experimen...
A number of potential runaway reaction systems of the fine chemical industry (e.g., polymerization p...
Abstract – Soft sensors are used widely to estimate a process variable which is difficult to measure...
International audienceAdaptive and high gain nonlinear observers are used for state and parameter es...
We propose a soft sensing method using local partial least squares models with adaptive process stat...
Nonlinear state estimation is a useful approach to the monitoring of industrial (polymerization) pr...
Online measurement of the melt index is typically unavailable in industrial polypropyleneproductionp...
An empirical model has been developed for the successful prediction of the melt index (MI) during gr...
Polymerization processes are important industrial processes where the polymer product can be made in...
Abstract: Since the online measurement of melt index (MI) of polyethylene is difficult, a virtual se...
A nonlinear reduced-order state observer is applied to estimate the degree of polymerization in a se...
State estimators, including observers and Bayesian filters, are a class of model-based algorithms fo...
This paper considers the development of multivariate statistical soft sensors for the online estimat...
In chemical processes, online measurements of all the process variables and parameters required for ...
This paper concerns nun-linear state estimation in a batch polymerization reactor where suspension p...
A moving-horizon inferential-state estimation technique is described which uses simulated "experimen...
A number of potential runaway reaction systems of the fine chemical industry (e.g., polymerization p...
Abstract – Soft sensors are used widely to estimate a process variable which is difficult to measure...
International audienceAdaptive and high gain nonlinear observers are used for state and parameter es...
We propose a soft sensing method using local partial least squares models with adaptive process stat...