A framework for extreme-event control in wastewater treatment.
(2002) In Water Science and Technology 45(4-5). p.299-308- Abstract
- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/107455
- author
- Rosén, Christian LU ; Larsson, M ; Jeppsson, Ulf LU and Yuan, Z
- organization
- publishing date
- 2002
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Water Science and Technology
- volume
- 45
- issue
- 4-5
- pages
- 299 - 308
- publisher
- IWA Publishing
- external identifiers
-
- wos:000174872000037
- pmid:11936647
- scopus:0036204225
- ISSN
- 0273-1223
- language
- English
- LU publication?
- yes
- id
- 477e1fd4-106b-4671-bb05-2b08ba86531a (old id 107455)
- alternative location
- http://www.ncbi.nlm.nih.gov:80/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11936647&dopt=Abstract
- date added to LUP
- 2016-04-04 09:26:13
- date last changed
- 2022-03-31 02:50:12
@article{477e1fd4-106b-4671-bb05-2b08ba86531a,
abstract = {{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.}},
author = {{Rosén, Christian and Larsson, M and Jeppsson, Ulf and Yuan, Z}},
issn = {{0273-1223}},
language = {{eng}},
number = {{4-5}},
pages = {{299--308}},
publisher = {{IWA Publishing}},
series = {{Water Science and Technology}},
title = {{A framework for extreme-event control in wastewater treatment.}},
url = {{http://www.ncbi.nlm.nih.gov:80/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11936647&dopt=Abstract}},
volume = {{45}},
year = {{2002}},
}