Synthesis of plantwide quality prediction system for a sintering plant

Michael Langer; Birgit Vogel

doi:10.3182/20020721-6-es-1901.01163

Synthesis of plantwide quality prediction system for a sintering plant

Michael Langer, Birgit Vogel

Bergische Universität Wuppertal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

To substantially improve operational control of complex industrial plants, it is important to be able to predict the influences which process variables have on quality-relevant target variables. The determination of influencing relationship and also the delay-time behaviour of various industrial processes makes it difficult to synthesis a quality prediction system. A hybrid modeling method combined with a suitable classification of process characteristics ensures a widespread model synthesis for quality prediction.

Original language	English
Title of host publication	IFAC Proceedings Volumes (IFAC-PapersOnline)
Editors	Gabriel Ferrate, Eduardo F. Camacho, Luis Basanez, Juan. A. de la Puente
Publisher	IFAC Secretariat
Pages	71-76
Number of pages	6
Edition	1
ISBN (Print)	9783902661746
DOIs	https://doi.org/10.3182/20020721-6-es-1901.01163
State	Published - 2002
Externally published	Yes
Event	15th World Congress of the International Federation of Automatic Control, 2002 - Barcelona, Spain Duration: 21 Jul 2002 → 26 Jul 2002

Publication series

Name	IFAC Proceedings Volumes (IFAC-PapersOnline)
Number	1
Volume	15
ISSN (Print)	1474-6670

Conference

Conference	15th World Congress of the International Federation of Automatic Control, 2002
Country/Territory	Spain
City	Barcelona
Period	21/07/02 → 26/07/02

Keywords

Design
Modeling
Neuro-Fuzzy
Process control
Simulation

Access to Document

10.3182/20020721-6-es-1901.01163

Cite this

Langer, M., & Vogel, B. (2002). Synthesis of plantwide quality prediction system for a sintering plant. In G. Ferrate, E. F. Camacho, L. Basanez, & J. A. de la Puente (Eds.), IFAC Proceedings Volumes (IFAC-PapersOnline) (1 ed., pp. 71-76). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 15, No. 1). IFAC Secretariat. https://doi.org/10.3182/20020721-6-es-1901.01163

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keywords = "Design, Modeling, Neuro-Fuzzy, Process control, Simulation",

author = "Michael Langer and Birgit Vogel",

note = "Publisher Copyright: Copyright {\textcopyright} 2002 IFAC.; 15th World Congress of the International Federation of Automatic Control, 2002 ; Conference date: 21-07-2002 Through 26-07-2002",

year = "2002",

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Langer, M & Vogel, B 2002, Synthesis of plantwide quality prediction system for a sintering plant. in G Ferrate, EF Camacho, L Basanez & JA de la Puente (eds), IFAC Proceedings Volumes (IFAC-PapersOnline). 1 edn, IFAC Proceedings Volumes (IFAC-PapersOnline), no. 1, vol. 15, IFAC Secretariat, pp. 71-76, 15th World Congress of the International Federation of Automatic Control, 2002, Barcelona, Spain, 21/07/02. https://doi.org/10.3182/20020721-6-es-1901.01163

Synthesis of plantwide quality prediction system for a sintering plant. / Langer, Michael; Vogel, Birgit.
IFAC Proceedings Volumes (IFAC-PapersOnline). ed. / Gabriel Ferrate; Eduardo F. Camacho; Luis Basanez; Juan. A. de la Puente. 1. ed. IFAC Secretariat, 2002. p. 71-76 (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 15, No. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - To substantially improve operational control of complex industrial plants, it is important to be able to predict the influences which process variables have on quality-relevant target variables. The determination of influencing relationship and also the delay-time behaviour of various industrial processes makes it difficult to synthesis a quality prediction system. A hybrid modeling method combined with a suitable classification of process characteristics ensures a widespread model synthesis for quality prediction.

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KW - Modeling

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KW - Simulation

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BT - IFAC Proceedings Volumes (IFAC-PapersOnline)

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Synthesis of plantwide quality prediction system for a sintering plant

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Keywords

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