Artificial neural network real-time process control system for small utilities

This article presents the final results from an Awwa Research Foundation project to implement an artificial intelligence real‐time automatic control system for a full‐scale dissolved‐air flotation (DAF) water treatment plant. The system developed through study used an artificial neural network to mo...

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Bibliographic Details
Published in:Journal - American Water Works Association 2007-06, Vol.99 (6), p.132-144
Main Authors: ZHANG, QING J., SHARIFF, RIYAZ, SMITH, DANIEL W., CUDRAK, AUDREY, STANLEY, STEPHEN J.
Format: Article
Language:English
Subjects:
Artificial Neural Networks
Automation
Coagulants
Compliance
Control algorithms
Control systems
Datasets
Drinking water
Effluents
Environmental regulations
Federal Regulations
Flotation
Monitoring systems
Neural networks
Process Control
Process controls
Real time
Small business
Software
State Regulations
Studies
Turbidity
Utilities
Water color
Water filtration
Water quality
Water Treatment
Water treatment plants
Water utilities
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Summary:This article presents the final results from an Awwa Research Foundation project to implement an artificial intelligence real‐time automatic control system for a full‐scale dissolved‐air flotation (DAF) water treatment plant. The system developed through study used an artificial neural network to model the DAF clarifier and was integrated with the plant supervisory control and data acquisition system for real‐time control. The system was found to be robust and flexible, and it adapted well to fast‐changing raw water conditions and different coagulants. Once established, the system ran the plant continuously, as if an expert were in control, providing quality drinking water with minimum operator intervention. The system was also capable of optimizing chemical dosage and reducing the costs of production.
ISSN:0003-150X
1551-8833
DOI:10.1002/j.1551-8833.2007.tb07961.x