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PubMed · 11936680

Model-based advanced process control of coagulation.

C W Baxter·R Shariff·S J Stanley·D W Smith·Q Zhang·E D Saumer
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Abstract

The drinking water treatment industry has seen a recent increase in the use of artificial neural networks (ANNs) for process modelling and offline process control tools and applications. While conceptual frameworks for integrating the ANN technology into the real-time control of complex treatment processes have been proposed, actual working systems have yet to be developed. This paper presents development and application of an ANN model-based advanced process control system for the coagulation process at a pilot-scale water treatment facility in Edmonton, Alberta, Canada. The system was successfully used to maintain a user-defined set point for effluent quality, by automatically varying operating conditions in response to changes in influent water quality. This new technology has the potential to realize significant operational cost saving for utilities when applied in full-scale applications.

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AlbertaAutomationEquipment DesignModels, ChemicalNephelometry and TurbidimetryNeural Networks, ComputerQuality ControlWaterWater Pollutants, ChemicalWater SupplyJournal ArticleResearch Support, Non-U.S. Gov't

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C W Baxter, R Shariff, S J Stanley, D W Smith, Q Zhang, E D Saumer. 2002. Model-based advanced process control of coagulation.. https://pubmed.ncbi.nlm.nih.gov/11936680/

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Risk factors for early-onset group B streptococcal disease in neonates: a population-based case-control study.

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