Early fault detection and diagnosis in chemical process monitoring represents a challenge to be overcome. Another one concerns the spatial overlapping problem among distinct fault classes, once some events may only be...
Early fault detection and diagnosis in chemical process monitoring represents a challenge to be overcome. Another one concerns the spatial overlapping problem among distinct fault classes, once some events may only be distinguished from the others by taking into account its order of occurrence. The hidden Markov model (HMM) technique is capable of providing information about the tendency of the process and of modelling ordered data. Hence, the goal is to investigate the contribution of this technique to both aspects related to process monitoring activities. The case study is based on the DAMADICS benchmark actuator system. Both abrupt and incipient faulty events were investigated. To the former, detection and diagnosis tasks were immediately satisfied; and to the latter, they were carried out in a progressive and correct course.
This paper presents fuzzy identification of two bioprocesses employing TSK-type models. A “Modified Gram-Schmidt” (MGS) orthogonal estimator is used to estimate the consequent parameters. This approach is then appli...
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This paper presents fuzzy identification of two bioprocesses employing TSK-type models. A “Modified Gram-Schmidt” (MGS) orthogonal estimator is used to estimate the consequent parameters. This approach is then applied to identify two distinct cases involving dissolved oxygen concentration: one related to a bioreactor and the other one related to an activated sludge process. The obtained models are then cross-validated.
Since most of the chemical processes are represented typically by nonlinear models, the use of nonlinear geometric control in chemical processes is straightforward. This paper presents a decoupling application in a pa...
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Since most of the chemical processes are represented typically by nonlinear models, the use of nonlinear geometric control in chemical processes is straightforward. This paper presents a decoupling application in a paper machine headbox. The nonlinear geometric control is implemented with blocks for reference trajectory, tracking error, integrators of error feedback and with an anti-windup scheme. The results show a clear implementation scheme and good dynamical responses.
A comprehensive model for the kraft pulping kinetics of Eucalyptus saligna hardwood is presented. Kinetic parameters were estimated by fitting the model to available experimental data taken from the literature over a ...
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A comprehensive model for the kraft pulping kinetics of Eucalyptus saligna hardwood is presented. Kinetic parameters were estimated by fitting the model to available experimental data taken from the literature over a range of process variables. The model takes into account the effect of hydroxide and sulfide concentration in the liquor as well as the temperature-time history of the cooking. Model predictions were successfully compared with an independent set of bench-scale plant data for lignin and carbohydrate dissolution. The model is able to predict quite well the trends of the process variables.
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