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A framework for extreme-event control in wastewater treatment.

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Author

Summary, in English

In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers. The methodology is illustrated in a simulation study.

Publishing year

2002

Language

English

Pages

299-308

Publication/Series

Water Science and Technology

Volume

45

Issue

4-5

Document type

Journal article

Publisher

IWA Publishing

Topic

  • Other Electrical Engineering, Electronic Engineering, Information Engineering

Status

Published

ISBN/ISSN/Other

  • ISSN: 0273-1223