Titlebook: Computational Intelligence Techniques for Bioprocess Modelling, Supervision and Control; Maria Carmo Nicoletti,Lakhmi C. Jain Book 2009 Sp

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,Drivers of Uncertainty — Empirical Results,ed and a dynamic model of the bioprocess can be established and (b) only basic operating signals, such as pH, base addition, stirrer speed, feed rates, can be measured on-line and it is difficult (or even impossible) to build a mechanistic model linking these variables. In the latter case, a neural

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Asymptomatic

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Lorenzo Marri-Malacrida,Emiliano Panconesig the information obtained from current and previous batches. The control policy updating is calculated using a model linearized around a reference batch. In order to cope with process variations and disturbances, the reference batch can be taken as the immediate previous batch. After each batch, th

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Software Sensors and Their Applications in Bioprocess, addition to the high costs associated with these measuring devices, their reliability can be poor when applied to large-scale systems. It is still the case that most industrial bioprocess control policies are based upon the use of infrequent off-line assay information for process operator supervisi

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Monitoring of Bioprocesses: Mechanistic and Data-Driven Approaches,ed and a dynamic model of the bioprocess can be established and (b) only basic operating signals, such as pH, base addition, stirrer speed, feed rates, can be measured on-line and it is difficult (or even impossible) to build a mechanistic model linking these variables. In the latter case, a neural

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Computational Intelligence Techniques for Supervision and Diagnosis of Biological Wastewater Treatmbtained from operational difficulties of one wastewater treatment plant cannot be easily generalized to another..Recent increased regulation over discharge of nutrients to receiving waterways, associated with operational difficulties of wastewater treatment plants, resulted in an increased need for

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Data Reconciliation Using Neural Networks for the Determination of KLa,work which has been previously trained to predict K.a from the series of oxygen conservation models. Results obtained with this new approach show that K.a can be predicted rapidly and gives values that are equivalent to those obtained with the conventional data reconciliation algorithm.

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Performance Monitoring and Batch to Batch Control of Biotechnological Processes,g the information obtained from current and previous batches. The control policy updating is calculated using a model linearized around a reference batch. In order to cope with process variations and disturbances, the reference batch can be taken as the immediate previous batch. After each batch, th

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